A Summary of the Major Issues, Important Theories,
Top Papers, Key Researchers, and Future Research
Problems of Management Information Systems
By
Dongjoo Kang, Fang Chen, Haidong Bi, Inder Singh, James Hwang,
Jennifer Xu, Jing Zhang, Jinwei Cao, Jongseo Kim, Kathy Broneck,
Matt Hacking, Ming Lin, Theo Song, Wei Gao, Wingyan Chung,
Yunchu Huang, and Zan Huang
For
Dr. Nunamaker’s MIS 696A Course
Fall Semester 2000
Table of Contents:
MIS Model .......................................................................................................................... 1
Artificial Intelligence .......................................................................................................... 2
Important Theories and Trends ....................................................................................... 2
Future Research .............................................................................................................. 2
Key People ...................................................................................................................... 3
Herbert A. Simon ........................................................................................................ 3
John McCarthy ............................................................................................................ 3
Raj Reddy.................................................................................................................... 3
Edward A. Feigenbaum .............................................................................................. 4
Roger C. Schank ......................................................................................................... 4
Hsinchun Chen ............................................................................................................ 4
Key Papers ...................................................................................................................... 4
CMC/HCI/Communication/Visualization .......................................................................... 6
Introduction ..................................................................................................................... 6
Most Important Theories................................................................................................. 6
Key Issues, Conflicts, And Major Research Problems ................................................... 6
Key Researchers.............................................................................................................. 6
Frank Biocca ............................................................................................................... 6
Robert Kraut................................................................................................................ 6
Jakob Nielsen .............................................................................................................. 7
Judy Olson .................................................................................................................. 7
Ben Shneiderman ........................................................................................................ 7
Sherry Turkle .............................................................................................................. 8
Joseph Walther ............................................................................................................ 8
Suzie Weisband........................................................................................................... 8
Key Papers ...................................................................................................................... 8
Computing Policy ............................................................................................................. 11
Introduction ................................................................................................................... 11
Most Important Theories............................................................................................... 11
Key Issues, Conflicts, and Major Research Problems .................................................. 11
Key Researchers............................................................................................................ 13
Barbara Simons ......................................................................................................... 13
Peter G. Neumann ..................................................................................................... 13
Seymour E. Goodman ............................................................................................... 13
Eli M. Noam.............................................................................................................. 14
Robert Kling.............................................................................................................. 14
Peter J. Denning ........................................................................................................ 15
Dorothy E. Denning .................................................................................................. 15
Pamela Samuelson .................................................................................................... 15
Sharon Eisner Gillett ................................................................................................. 16
Key Papers .................................................................................................................... 16
Database ............................................................................................................................ 18
Introduction ................................................................................................................... 18
Key Theories ................................................................................................................. 18
i
Key Issues ..................................................................................................................... 18
Future Research ............................................................................................................ 18
Key Researchers............................................................................................................ 19
Peter P. Chen ............................................................................................................. 19
Edgar F. Codd ........................................................................................................... 19
Won Kim................................................................................................................... 19
Stuart E. Madnick ..................................................................................................... 19
Salvatore T. March.................................................................................................... 20
Sudha Ram ................................................................................................................ 20
Joseph S. Valacich .................................................................................................... 21
Key Papers .................................................................................................................... 21
E-Commerce ..................................................................................................................... 23
Introduction ................................................................................................................... 23
Key Issues, Conflicts, and Major Research Problems .................................................. 23
Key Researchers............................................................................................................ 24
Lynda M Applegate .................................................................................................. 24
Andrew B. Whinston ................................................................................................ 24
Vladimir Zwass ......................................................................................................... 24
Yannis Bakos ............................................................................................................ 25
Haim Mendelson ....................................................................................................... 25
Key papers .................................................................................................................... 25
Group Support System (GSS) ........................................................................................... 27
Introduction and Key Theories ..................................................................................... 27
Key Issues and Conflicts ............................................................................................... 27
Major Research Problems in the Future........................................................................ 27
Key Researchers............................................................................................................ 28
Jerry DeSanctis ......................................................................................................... 28
R. Brent Gallupe ....................................................................................................... 28
Sara Kiesler ............................................................................................................... 28
Jay F. Nunamaker, Jr. ............................................................................................... 29
Wanda J. Orlikowski................................................................................................. 29
Judy Olson ................................................................................................................ 29
Sirkaa L. Jarvenpaa ................................................................................................... 30
Douglas R. Vogel ...................................................................................................... 30
Key Papers .................................................................................................................... 30
Information Economics ..................................................................................................... 33
Key Issues and Conflicts ............................................................................................... 33
Most Important Theories............................................................................................... 33
Key Researchers............................................................................................................ 34
Erik Brynjolfsson ...................................................................................................... 34
Charles H. Kriebel .................................................................................................... 34
Tridas Mukhopadhyay .............................................................................................. 34
Andrew B. Whinston ................................................................................................ 34
Key papers .................................................................................................................... 34
Information Retrieval ........................................................................................................ 38
Key Issues ..................................................................................................................... 38
ii
Trends ........................................................................................................................... 38
Key People .................................................................................................................... 38
Gerard Salton ............................................................................................................ 38
Karen Sparck Jones ................................................................................................... 38
Gary Marchionini ...................................................................................................... 39
Edward A. Fox .......................................................................................................... 39
W. Bruce Croft .......................................................................................................... 39
Key Papers .................................................................................................................... 39
Knowledge Management .................................................................................................. 41
Introduction ................................................................................................................... 41
Categories of Knowledge Management Research ........................................................ 41
Key Theories and Methodologies ................................................................................. 42
Key Issues ..................................................................................................................... 42
Future Research Trends ................................................................................................ 42
Key Researchers............................................................................................................ 42
Christine L. Borgman................................................................................................ 42
Hsinchun Chen .......................................................................................................... 42
W. Bruce Croft .......................................................................................................... 43
Daniel E. O'Leary ..................................................................................................... 43
Gerard Salton ............................................................................................................ 43
Key Articles .................................................................................................................. 43
Operation Research ........................................................................................................... 46
Introduction ................................................................................................................... 46
Key People .................................................................................................................... 46
Hau L. Lee ................................................................................................................ 46
Marshall Fisher ......................................................................................................... 46
James B. Orlin ........................................................................................................... 47
George Nemhauser.................................................................................................... 47
Ellis Johnson ............................................................................................................. 47
Moshe Dror ............................................................................................................... 47
Key Papers .................................................................................................................... 47
Social/Ethical/Psychological Issues .................................................................................. 50
Introduction ................................................................................................................... 50
Most Important Theories............................................................................................... 50
Key Issues, Conflicts, and Major Research Problems .................................................. 50
Key Researchers............................................................................................................ 51
Mary J. Culnan .......................................................................................................... 51
Sara Kiesler ............................................................................................................... 51
Robert Kling.............................................................................................................. 51
Donald Norman ......................................................................................................... 51
Gary Olson ................................................................................................................ 52
Lee Sproull ................................................................................................................ 52
Key Papers .................................................................................................................... 52
Supply Chain Management ............................................................................................... 55
Most Important Theories............................................................................................... 55
Key Issues and Conflicts ............................................................................................... 55
iii
Key researchers ............................................................................................................. 56
Gerard P. Cachon ...................................................................................................... 56
Fangruo Chen ............................................................................................................ 56
Hau L. Lee ................................................................................................................ 56
Paul H. Zipkin ........................................................................................................... 56
Key papers .................................................................................................................... 56
Systems Analysis and Design ........................................................................................... 59
Key Issues ..................................................................................................................... 59
Key Researchers............................................................................................................ 59
Tom DeMarco ........................................................................................................... 59
Grady Booch ............................................................................................................. 59
Michael Fagan ........................................................................................................... 60
Roger S. Pressman .................................................................................................... 60
Watts S. Humphrey ................................................................................................... 60
Edward Yourdon ....................................................................................................... 61
Key Papers/Books ......................................................................................................... 61
Telecommunication........................................................................................................... 63
Key Theories and Issues ............................................................................................... 63
Future Work .................................................................................................................. 63
Key Researchers............................................................................................................ 63
Robert E. Kahn.......................................................................................................... 63
Ted Nelson ................................................................................................................ 64
David Clark ............................................................................................................... 64
Deborah Estrin .......................................................................................................... 65
Roch Guerin .............................................................................................................. 65
Key Articles .................................................................................................................. 65
Workflow .......................................................................................................................... 68
Introduction ................................................................................................................... 68
The Evolution of Workflow .......................................................................................... 68
Trends ........................................................................................................................... 68
Key People .................................................................................................................... 69
Christoph Bussler ...................................................................................................... 69
Clarence Ellis ............................................................................................................ 69
Stefan Jablonski ........................................................................................................ 69
Amit P. Sheth ............................................................................................................ 69
J. Leon Zhao.............................................................................................................. 69
Key Papers .................................................................................................................... 70
Appendix A ....................................................................................................................... 72
iv
MIS Model
Management Information Systems is one of the most dynamic fields of study in
academia. In comparison to other fields of study, it is a young, applied research
discipline. However, what exactly is MIS? Elements of MIS may include computerbased systems, networks, people, processes, data, and software. This paper proposes that
MIS is a new and previously unknown junction of reference disciplines. Many reference
disciplines tend to conduct more basic research while MIS performs more applied
research. The reference disciplines for MIS include Electrical and Computer
Engineering, Computer Science, Management and Organizational Behavior, Systems and
Industrial Engineering, Cognitive Psychology, and Economics.
How does MIS relate to reference disciplines? Some reference disciplines, such as
accounting, management, and economics, are related to business and compete more
directly with MIS for resources and credibility. However, MIS does something no
reference discipline does, or it wouldn't exist at all! As will be shown by the following
review of major issues, important theories, top papers, key researchers, and future MIS
research areas, MIS integrates many disciplines.
MIS
CS
KM
AI
IR
DB
Telecom
EC
EE
ORG
GSS
SS
WF
CMC/HCI/VIS
Soc/Eth/Psy
Policy
Info Econ
ECON
OR
MS
Overview of MIS
Artificial Intelligence
Important Theories and Trends
The original goal of AI (Artificial Intelligence) is to understanding and implementing
intelligence. Herbert A. Simon further paints a broad picture of AI as a discipline
constantly pursuing computational creations that challenge the uniqueness of biologically
grounded intelligence. John McCarthy gives 12 branches of AI, namely, logic, learning,
searching, representation, pattern recognition, inference, common sense knowledge,
planning, epistemology, ontology, heuristics, and genetic programming.
The controversies of AI fall into the following three major categories:
(1) Knowledge representation and reasoning:
A longstanding view of the role of logic in AI is that logic is an abstracted, hence simpler
form of natural language. Thus it provides an ideal medium for a first approximation.
This view is attacked with a variety of arguments [Wolfgang Bibel].
Drew McDermott argues that AI’s success arises not from sophisticated representation
and reasoning methods, but rather from simple representations and tractable algorithms.
Another controversy concerning knowledge representation and reasoning is whether
intelligence is derived primarily from logical reasoning or from knowledge. The
controversy is not about whether common sense is necessary but how much it should be
built into the logic or into the knowledge base [Bruce Buchanan].
(2) Machine learning:
The problem is whether computers should attempt to model how people or whether
computers should follow methods did that no person things that no person could ever do
and that might actually improve on people. [Roger Schank]. Oliver Selfridge suggests
that AI software should be more concerned with being changeable than with satisfying
specifications.
(3) The practice of AI:
There is a conflict between methodology-driven and phenomenon-driven research in AI,
as well as the conflict between quantitatively valuable research and the more creative and
often less quantifiable research necessary for a constantly growing discipline [Jerry
Feldman].
Future Research
(1) The decline in complex knowledge representations and the success of prepositional or
probabilistic competitors [Drew McDermott];
(2) Machine learning and automation of deductive reasoning [Donld Michie].
2
(3) Building intelligent systems that will let people access and utilize enormous amounts
of information generated by modern societies in various forms for making informed
decisions [Ryszard Michalski].
(4) Multi-Agent Systems, application for data mining, knowledge Management.
Key People
Herbert A. Simon
Description
Professor, Carnegie-Mellon University, Pittsburgh, PA
Alfred Nobel Memorial Prize in Economic Sciences in 1978 for
"pioneering research into the decision-making process within economic
organizations”
ACM: AM Turing Award, 1975
Research interests
Building and testing theories of human cognition, using computer
simulation models. The usage of different representations to draw
inferences from information, especially reasoning from
diagrammatically and pictorially presented information, and comparing
the effectiveness for communication purposes of different
representations.
John McCarthy
Description
Professor of Computer Science at Stanford University
The inventor of LISP. ACM/A.M. Turing Award, 1971.
Research Interests
His research is mainly in artificial intelligence. Long ago he originated
the Lisp programming language and the initial research on general
purpose time-sharing computer systems
Raj Reddy
Description
Herbert A. Simon University Professor, Computer Science and
Robotics in the School of Computer Science at CMU.
He served as the founding Director of the Robotics Institute from 1979
to 1991. He served as the Dean of School of Computer Science at CMU
from 1991 to 1999. He was awarded the ACM Turing Award in 1994
Research Interests
Dr. Reddy's research interests include the study of human-computer
interaction and artificial intelligence. His current research projects
include spoken language systems; invisible computing, gigabit
networks; universal digital libraries; and distance learning on demand
3
Edward A. Feigenbaum
Description
Professor of Computer Science and Co-Scientific Director of the
Knowledge Systems Laboratory at Stanford University.
Dr. Feigenbaum served as Chief Scientist of the United States Air
Force from 1994 to 1997. He was a recipient of the 1994 ACM Turing
Award.
Research Interests
Knowledge-Based Systems Research and Applications; Computer
Industry Research; Defense Technology and Technology Policy
Roger C. Schank
Description
Roger C. Schank, director of the Institute for the Learning Sciences (ILS)
at Northwestern University, is a leader in the field of artificial
intelligence and multimedia-based interactive training.
Research Interests
His work stresses the value of learning from experts, developing skills
rather than perfecting routines, and applying the benefits of "just-in-time"
training
Hsinchun Chen
Background
Professor, MIS Department. University of Arizona
He received the Ph.D. degree in Information Systems from New York
University in 1989. He is author of more than 70 articles covering semantic
retrieval, search algorithms, knowledge discovery, and collaborative
computing in leading information technology publications.
Research Interests
Digital Libraries, Knowledge Management, Multi-lingual and Distributed Information
Retrieval
Key Papers
Computer Machinery and Intelligence, A. M. Turing
This paper address the question of “Can machine think?” Turing takes a behavioristic
posture relative to the question. The question is to be decided by an unprejudiced
comparison of the alleged “thinking behavior” of the machine with normal “think
behavior” of human beings. hw propose an experiment-commonly called “Turing test”-in
which the unprejudiced comparison could be made. Though the test has flaws, it is the
best that has been proposed to date.
Understanding The Natural and the Artificial Worlds, Herbert A. Simon. The Science of
Artificial Intelligence, 1996, pp 1-24.
Understanding the natural and the artificial worlds, The psychology of thinking:
embedding artifice in nature, The science of design: creating the artificial, The
4
architecture of complexity. "Artificial" denotes systems that have a given form and
behavior because they adapt to their environment in reference to goals or purposes.
Some Philosophical Problems from the Standpoint of Artificial Intelligence, John
McCarthy and Pat Hayes, 1969 in Machine Intelligence 4.
It is the basic paper on situation calculus. This paper looks at some philosophical issues
concerning artificial intelligence, which includes how the concept of ability and belief
could be given formal definition in the metaphysically adequate automaton model and
indicates the correspondence between these formal concepts and the corresponding
commonsense concepts, construction of epistemologically adequate system. Instead of
given formal definitions, formal notions are introduced by informal natural language
descriptions with examples of their use to describe situations and possibilities for action
they present.
Intelligence without Robots, oren Etzioni, AI Magazine, Winter 1993, vol. 14, no. 4, pp.713.
In his recent papers, entitled "Intelligence without Representation and "Intelligence
without Reason," Brooks argues for studying complete agents in real-world environments
and for mobile robots as the foundation for AI research. This article argues that, even if
we seek to investigate complete agents in real-world environments, robotics is neither
necessary nor sufficient as a basis for AI research. The article proposes real-world
software environments, such as operating systems or databases, as a complementary
substrate for intelligent-agents research, and considers the relative advantages of software
environments as test beds for AI.
Natural Language Processing, Roger C. Schank, Eugene Charniak, Yorick Wilks, Terry
Winograd, William A. Woods: IJCAI 1977: 1007-1013
5
CMC/HCI/Communication/Visualization
Introduction
Computer-mediated-communication (CMC), human-computer-interaction (HCI),
communication and visualization of design interface impacts the research within MIS.
This body of literature’s research tries to understand how humans interact and
communicate with one another using different computerized technologies. It is important
to understand how people interact with the computer and with one another in order to
better understand prototypes that MIS researchers may design. The communication
amongst these modes needs to also be taken into consideration as research has suggested
that decisions, communication, and usage of technologies differ via computers than in
face-to-face (FTF) settings.
Most Important Theories
Some important theories, hypothesis, and models to come from this area of research are
Interactivity Model, The Postrepresentational Model (HCS), Artificial Morality, SIDE
Theory.
Key Issues, Conflicts, And Major Research Problems
The current key issues in this area are the visualization of dynamic processes in network
and the interaction metaphor for dynamic processes. It consists of the integration of
tactile sensing, vision, and sound.
Key Researchers
Frank Biocca
Contact Information
404 Communication Arts and Sciences
Michigan State University
Department of Communications
East Lansing, MI
(517) 355-5073; e-mail: biocca@msu.edu
Research areas
Dr. Biocca studies computer design and visualizations. He is a leader in research
surrounding multi-modal sensory information. The focus of his research is being able to
understand if when interfaces become more anthropomorphic and/or interactive if users
engage in higher levels of consciousness.
Robert Kraut
Contact Information
3515 Newell-Simon Hall
Carnegie Mellon University
6
5000 Forbes Avenue
Pittsburgh, PA 15213-3891
(412) 268-7694; e-mail: robert.kraut@cmu.edu
Research areas
Dr. Kraut studies emerging information technologies and how they in turn affect human
communication. Specifically, he focuses on individuals and organizations performance
in coordinating tasks, prototyping designs, Video communication systems, and
technology on quality of work. Currently, Dr. Kraut is working on the influence of
networks and communication technology. He is also involved in the HomeNet project.
Jakob Nielsen
Contact Information
2704 Fairbrook Dr.
Mountain View, CA 94040
E-mail: jakob@useit.com
Research areas
Currently he is working on the designs of websites and information architecture and task
design. He has published in the ACM, serves on journal editorial boards, and was listed
as one of the web’s most influential people.
Judy Olson
Contact Information
University of Michigan
701 Tappan Street
C-2420 Bus. Ad.
Ann Arbor, MI. 48109-1234
(734) 647-4606; e-mail: jsolson@umich.edu
Research areas
Her focus is on Human-computer-interaction and the design and evaluation issues of
software. She has worked for Bell laboratories and is currently a Professor in the School
of Information. Her achievements include over 50 books and articles involving human
psychology, computers, and visualization design.
Ben Shneiderman
Contact information
Department of Computer Science
University of Maryland
College Park, MD 20742
(301) 405-2680; e-mail: ben@cs.umd.edu
Research areas
Dr. Shneiderman’s research pertains to areas involving human-computer-interaction and
psychology. He also participates in visualization information representation and design.
His achievements include being a Fellow of the ACM, the founding director of Human
Computer Interaction Laboratory, and hosting an annual satellite presentation of User
Interface Strategies.
7
Sherry Turkle
Contact Information
Program in Science, Technology, and Society, MIT
E51-296c
77 Massachusetts Ave.
Cambridge, MA 02139-4307
(617) 253-4068; e-mail sturkle@media.mit.edu
Research areas
Dr. Turkle has been researching communication on the Internet along with psychological
impacts of computational objects. Her interests have involved computer culture,
sociology, and psychology with regards to new technologies, specifically the Internet.
Her research has been funded by organizations such as the NFS, Guggenheim
Foundation, and the Rockefeller Foundation.
Joseph Walther
Contact Information
Dept. of Language, Literature, and Communication
Rensselaer Polytechnic Institute
110 8th Street
Troy, NY 12180-3590
(518) 276-2557; e-mail: walthj@rpi.edu
Research areas
His research focuses on computer-mediated-communication and its effects in teaching,
teams and social relationships. He draws in psychological and social issues of Internetbased communication into collaborative work across countries. Dr. Walther has won
awards in NCA for his works on technological communities and interpersonal
communication.
Suzie Weisband
Contact Information
Department of Management Information Systems
Eller College of Business and Public Administration
The University of Arizona
Tucson, Arizona 85721
(520) 621-8303; E-mail: weisband@bpa.arizona.edu
Research areas
Dr. Weisband’s research includes social and behavioral impacts of technology on people.
She has participated in research involving communication among groups using various
technological platforms and interactivity. Dr. Weisband has also been involved in GSS
research, F-t-F interactions, and melding disciplines such as MIS, Communication,
Sociology, and Psychology into her research.
Key Papers
8
Biocca, F., Kim, T., and Levy, M. R. (1995). Chapter 1: The vision of virtual reality. In
F. Biocca’s Communication in the age of virtual reality (pp. 3-14). Hillsdale, NJ:
Erlbaum.
The chapter looks at if virtual reality would make for a better medium of communication.
They suggest that VR is the ultimate form of media technology. If this is the case, MIS
researchers need to look at different areas of design integrating VR.
Daft, R. L. and Lengel, R. H. (1986). Organizational information requirements, media
richness and structural design. Management Science, 32(5), 554-571.
The article primarily discusses that uncertainty and equivocality are the primary factors
why organization processes information. It attempted to integrate equivocality with
uncertainty and argue that structural characteristics are used to help organization to cope
with these two factors. The authors proposes models that show how organization can be
design to meet the information needs of technology, interdepartment relations, and the
environment.
Galagher and Kraut. (1994). Computer mediated communication for intellectual
teamwork. Information Systems Research, 5(2), 110-138.
This article analyzes contingency theory’s prediction that using computer mediated
communication to accomplish complex collaboration work will be difficult, especially for
tasks that require interactive, expressive communication. The author conducted
experiments with sixty-seven three person groups of students that completed two
collaborative writing projects under either computer only, computer plus phone or face to
face communications. The findings tend to confirm the contingency hypothesis regarding
the difficulty of accomplishing work that involves ambiguous goals, multiple
perspectives, and information that is susceptible to multiple interpretations without an
interactive multiperson communication medium, such as face-to-face meetings.
Kramer, R. and Tyler, T. (1996). Trust in organizations: Frontiers of theories and
research. Sage Publications
Laudauer, T. K. (1995). The troubles with computers: Usefulness, usability, and
productivity. MIT Press, Cambridge, MA.
The book explains and illustrates why computers are in trouble and why investments on
computing have not resulted in productivity. The author argues that the conditions are the
result of the fact that computers rarely improve efficiency of the information work
because they are too hard to use and do too little that is sufficiently useful. The author
proposed that the use of user centered development technique through task analysis,
iterative design, trial use, and evaluation, computer systems can be powerful tools.
Reeves and Nass. (1996). The media equation : How people treat computers, television,
and new media like real people and places. Cambridge University Press, Cambridge, UK.
The book involves numerous studies conducted by Reeves and Nass to understand how
people treat media such as computers, television, and other new technologies. They found
that people tend to have biases and opinions about the medium they are interacting with.
Changes in voice or display can result in the changes of attitudes towards the mechanism
9
they are interacting with. While there has been much academic discussion as to whether
or not the results found in the book are correct, it poses an area of research that had not
been looked at before that MIS researchers should be aware of. If there is truth to the
findings of people, then how MIS designs systems needs to be wary of the findings. If
people respond in different ways to small characteristics such as male versus female
voice and credibility attributions of interactions that ensue, then small design issues of
choosing voice automated systems can impact user satisfaction.
Sproull, L. and Kiesler, S. (1991). Connections: New waysof working in the networked
organization. MIT Press, Cambridge, MA.
Within the book, the authors demonstrate the effect of new technologies in organizational
communication and how people's thinking and working habits change in lieu of these
technologies. They give guideline criteria as to how people utilize technology, such as email, to form better networks and how visions and goals of the organization should in
turn be shaped. The book gives a good basis for understanding users within an
organization, what impact inventions can have on a user, and the different characteristics
of how people use the technology. Since MIS involves organizations and communicative
functions within, understanding how their prototypes and designs effect an organization
and its people is beneficial. When designing prototypes, audience characteristics need to
be taken into consideration.
Walther, J. (1995). Relational aspects of CMC: Experimental observations over time.
Organization Science, 6( 2), 186-203.
This article looked at computer conferencing and its effects on people's perceptions of the
relational messages found within. Dr. Walther suggests that past research about CMC
relational research is inconsistent and that some areas of interpersonal communication are
actually better when done over CMC than in face-to-face groups. It is important for MIS
researchers to understand when it is better to engage in group work over CMC versus
face-to-face to achieve better results in their proposed designs for task related situations.
10
Computing Policy
Introduction
The discipline is not well established till present. Papers in this field can be found in
many journals such as Communication of the ACM, Computers andSociety, Science,
Technology and Human Values, and etc. But there is no key journal for this filed, which
is also true for debate about the social roles of information technology as mentioned in
Rob Kling’s book, Computerization and Controversy: Value Conflicts and Social
Choices.
The discipline is closely related to research in social and ethics issues of computing,
which is come from the close relationship between social science, ethics and policy
science. Rob Kling divided theoretical perspectives adopted by Social Analysts of
Computing into two major categories, and Policy research was included into this scheme.
Social Analysis of Computing
Systems Rationalism
Rational
Structural
Human Relations
Segmented Institutionalism Interactionist
Organizational Politics
Class Politics
The suitable definition for “policy” from Webster for this domain is “a high-level overall
plan embracing the general goals and acceptable procedures especially of a governmental
body ”. Policy issues research is different from social and ethics issues research. Social
and ethics research focus on the roles of information technology in social or ethical
settings, and policy research focuses on the high-level relationship between different
participants/actors in the social environment, and power and goal are the key issues.
Government is usually involved in research of this discipline, and because of the
difference between different countries on social organization and government roles,
international view should be taken to describe the who picture.
Most Important Theories
Theories in this field is from economics, policy and technology, and it is hard to address
key theories for this not well defined field.
Key Issues, Conflicts, and Major Research Problems
Universal Access
Intellectual Property
Encryption and Computer Security
Free Speech and the Internet
Funding for Scientific Research
11
Privacy
Electronic Commerce: Taxation, Supply chain/Industrial structure
Policy aspects (WTO, International Telecommunication Union, Federal Communications
Commission, Harmonization)
Regulatory Frameworks
General Political Milieu
The role of the state/government
From TIPI(Telecommunications and Information Policy Institute, University of Texas,
Austin TX 78712, USA)
Emerging Issues in the International Telecommunications and Information Environment:
Research Topics
1. TELECOMMUNICATIONS *
A. Policy Aspects *
World Trade Organization *
International Telecommunication Union *
Federal Communications Commission *
Special focus: Harmonization *
B. Access and Equity *
Universal Access *
Digital Divide *
C. Subsidies *
D. Regulatory Frameworks *
E. General Political Milieu *
F. The role of the state/government *
G. Structure *
H. Rates *
I. Procurement *
J. Technologies *
Convergence *
Innovation *
K. Services *
2. INNOVATION CLUSTERS/TECHNOPOLES *
A. Space and Place *
B. Agglomeration *
Institutional Frameworks *
Other importance factors include: *
Cultural Conditions *
Demand *
"Environmental" Conditions *
Labor *
C. Agglomeration is not a sufficient condition *
D. Software Development *
3. ELECTRONIC COMMERCE *
A. Space/Place *
12
B. Taxation *
C. Supply chain/ Industrial structure *
D. Technological Bases *
Transaction Security *
Privacy *
E. Intellectual Property *
Key Researchers
Barbara Simons
simons@acm.org , http://barbara.simons.org
Dr. Simons was elected President of ACM in 1998, the same year in which she
also won the Electronic Frontier Foundation Pioneer Award. Selected by c-net in
1995 as one of its 26 Internet "Visionaries," and named one of the "Top 100
Women in Computing" by Open Computing in 1994, she holds several patents
and has authored numerous technical papers. Dr. Simons is a member of the President's
Export Council's Subcommittee on Encryption and is also a Fellow of ACM and the
American Association for the Advancement of Science.
Education
Ph.D. in computer science from the University of California, Berkeley, in June 1981 thesis advisor Richard Karp. My dissertation, Scheduling with Release Times and
Deadlines, solved a major open problem in scheduling by developing the first known
algorithm for the problem.
Research areas
Policy Issues, Scheduling Theory, Compiler Optimization, Fault Tolerant Distributed
Computing, Communicating Sequential Processes
Peter G. Neumann
Principal Scientist at SRI International Computer Science Laboratory
http://www.csl.sri.com/neumann/neumann.html
Neumann@csl.sri.com
Education
He spent eight years at Harvard (1950-58, with his A.B. in Math in 1954, S.M. in Applied
Math in 1955, and PhD in 1961 after returning from his two-year Fulbright in Germany
(1958-60), where he received the German Dr rerum naturarum in 1960.
Research areas
His main research interests continue to involve security, crypto applications, overall
system survivability, reliability, fault tolerance, safety, software-engineering
methodology, systems in the large, applications of formal methods, and risk avoidance.
Seymour E. Goodman
goodman@cc.gatech.edu
Seymour (Sy) E. Goodman has been Professor of MIS (1981) and a member of
the Center for Middle Eastern Studies at the University of Arizona, and
Carnegie Science Fellow (1994) and head of the Program on the Information
Technologies and International Security at the Center for International Security
13
and Arms Control, Stanford University. Earlier tenured and visiting appointments have
been at the University of Virginia (Applied Mathematics and Computer Science),
Princeton University (Mathematics and the Woodrow Wilson School of Public and
International Affairs), and the University of Chicago (Economics).
Education
He did his undergraduate work at Columbia University, and obtained his Ph.D. from the
California Institute of Technology.
Research Areas
Prof. Goodman's research interests include international developments in the information
technologies (IT), technology diffusion, IT and national security, and related public
policy issues. Areas of geographic interest include the former Soviet Union and Eastern
Europe, Latin America, the Middle East, Southeast Asia, and parts of Africa. Earlier
research had been in areas of statistical and continuum physics and combinatorial
algorithms.
Eli M. Noam
noam@columbia.edu
http://www.citi.columbia.edu/elinoam
Director, Columbia University Institute for Tele-Information; 1983-1987, 1991present
Professor of Finance and Economics, Columbia Business School; 1976-present
Education
Harvard: A.B. 1970 (Phi Beta Kappa); A.M. 1972; J.D. 1975; Ph.D. Economics, 1975,
Dissertation adviser: Martin Feldstein.
Research Areas
Communications, information, public choice, public finance, and general regulation.
Robert Kling
kling@indiana.edu
http://www.slis.indiana.edu/kling/
In August 1996, he moved to Indiana University - Bloomington as Professor of
Information Science and Information Systems. He directs a new
interdisciplinary research center at IU, the Center for Social Informatics and
also directs the Master of Information Science degree program.
Between 1966 and 1971 he held a research appointment in the Artificial Intelligence
Center at the Stanford Research Institute. He held his first professorship in Computer
Science at the University of Wisconsin-Madison between 1970-1973. He was on the
faculty of UC-Irvine from 1973-1996 and held professorial appointments at UCI's Center
for Research on Information Technology and Organizations and Graduate School of
Management.
Education
He completed his undergraduate studies at Columbia University (1965) and his graduate
studies, specializing in Artificial Intelligence, at Stanford University (1967, 1971).
Research Areas
Social Informatics; Organizational Informatics; Information Systems; Information
Technology and Social Change
14
His research focuses upon the social consequences of computerization and the social
choices that are available to people. He has studied these issues in and around
organizations that have invested in various information systems, desktop computing,
computerized manufacturing environments, digital libraries, instructional computing, etc.
He believes that we have to understand information technologies in terms of their
associated social structures and politics, and in meaningful social contexts -- not just as
"information tools."
Peter J. Denning
pjd@cs.gmu.edu
http://www.cs.gmu.edu/faculty/denning/
Peter J. Denning is Professor of Computer Science and University Coordinator
for Process Reengineering at George Mason University. Since joining GMU in
1991, he served as vice provost for continuing professional education, associate
dean for computing, and chair of the Computer Science Department in the School
of Information Technology and Engineering. He is founding director emeritus of
the Hyperlearning Center, formerly the Center for the New Engineer, which he founded
in 1993.
Research Areas
Operating Systems, Workflow Management, High Performance Computing, Security,
Performance Modeling
Dorothy E. Denning
denning@georgetown.edu.
http://www.cs.georgetown.edu/~denning/
Dorothy E. Denning is professor of Computer Science at Georgetown University
and director of the Georgetown Institute for Information Assurance. She is also
affiliated with the Communication, Culture and Technology program and the
Science and Technology in International Affairs program. Her area of specialty is
information warfare and information assurance.
Research Areas
Information warfare and information assurance
Education
B.A. and M.A. degrees in mathematics from the University of Michigan, Ph.D. degree in
computer science from Purdue University
Pamela Samuelson
pam@sims.berkeley.edu
http://www.sims.berkeley.edu/~pam/
Pamela Samuelson is a Professor at the University of California at Berkeley with a
joint appointment in the School of Information Management and Systems and the School
of Law. She is also Co-Director of the Berkeley Center for Law and Technology.
Research Areas
Intellectual Property Law, Copyright Law
15
Education
Yale Law School: J. D. 1976, University of Hawaii at Honolulu: M. A. 1972, Political
Science, B. A. 1971, History
Sharon Eisner Gillett
Sharon Eisner Gillett is the Executive Director of the MIT Internet and Telecoms
Convergence Consortium and a Research Associate at the MIT Center for
Technology, Policy, and Industrial Development. Ms. Gillett is the author of
numerous articles about the Internet and telecommunications, including,
"Connecting Homes to The Internet: An Engineering Cost Model of Cable vs. ISDN,"
and "The Self-Governing Internet: Coordination by Design" (with Mitchell Kapor). From
1982-92 she worked as a software engineer and manager at BBN Communications Corp.
and Thinking Machines Corp.
Research
Telecommunication Policy
Education
Ms Gillett received her MBA and MS in Technology and Policy from MIT in 1995, and
her AB in Physics from Harvard-Radcliffe in 1982.
Key Papers
Social Analyses Of Computing - Theoretical Perspectives In Recent Empirical-Research
Kling R. Computing Surveys. 12: (1) 61-110 1980, 172.
The Global Diffusion Of The Internet - Patterns And Problems
Goodman Se, Press Li, Ruth Sr, Rutkowski Am Communications Of The ACM
37: (8) 27-31 Aug 1994 14
This paper concerns about the international diffusion of the internet technology. Several
models are identified to cover most of the forms of international proliferation of Internet
technology. Patterns identified include building national backbones, grass root nets,
commercial carriers and resellers. Issues about the impediments to network diffusion are
also addressed in this paper.
Computerization And Social Transformations. Kling R. Science Technology and Human
Values. 16: (3) 342-367 SUM 1991, 31.
This paper examines the relationship between the use of computer-based systems and
transformations in parts of the social order. Answers to this question rest heavily on the
way computer-based systems are consumed -- not just produced or disseminated. The
discourse about computerization advanced in many professional magazines and the mass
media is saturated with talk about "revolution" -- and yet, substantial social changes are
often difficult to identify in carefully designed empirical studies. The paper examines
qualitative case studies of computerization in welfare agencies, urban planning,
accounting, marketing, and manufacturing to examine the ways that computerization
alters social life in varied ways: sometimes restructuring relationships and in other cases,
reinforcing existing social relationships. The paper also examines some of the theoretical
16
issues in studies of computerization, such as drawing boundaries. It concludes with some
observations about the sociology of computer science as an academic discipline.
17
Database
Introduction
Database systems continue to be a key area in many fields including business, computer
science, and engineering. Representing knowledge within a computer is one of the central
challenges of the field. Database research has focused primarily on this fundamental
issue. Many universities have faculty investigating these problems and offer courses that
teach the concepts developed by this research program. Today, the Internet is considered
by many to be one large database. Database research has migrated from a study of data
modeling for a centralized data store, to studies on highly distributed, heterogeneous,
dynamic, and enormous collections of multimedia data.
Key Theories
E.F. Codd and Peter Chen developed several early key theories in database research. E.F.
Codd developed the relational model for databases and Peter Chen introduced the entityrelationship model. These theories are covered in greater detail under the respective
researcher. More recent database theories adopt an object-oriented design and respond to
the effects of distributed databases, such as the Internet, and larger and faster data storage
capabilities.
Key Issues
There continues to be active and valuable research on representing and indexing data,
adding inference to data search, compiling queries more efficiently, executing queries in
parallel, integrating data from heterogeneous data sources, analyzing performance, and
extending the transaction model to handle long transactions and workflow (transactions
that involve human as well as computer steps). The availability of very-large-scale
(tertiary) storage devices has prompted the study of models for queries on very slow
devices.
Future Research
There is great interest and direction in unifying object-oriented concepts with the
relational model. New data types (image, document, drawing) are best viewed as the
methods that implement them rather than the bytes that represent them. By adding
procedures to the database system, one gets active databases, data inference, and data
encapsulation. This object-oriented approach is an area of active research in academe and
in industry. Continuing research is creating the ideas and training the people for the next
product generation. As storage devices continue to become larger and faster, new data
models will need to be developed to efficiently represent and process the data. The
development of ultra-high-density data storage such as holographic data storage is a
promising innovation in the field of database research.
18
Key Researchers
Peter P. Chen
Contact Information
Louisiana State University, Department of Computer Science
298 Coates Hall
Baton Rouge, LA 70803, USA
(225) 578-2483; chen@bit.csc.lsu.edu
Research areas
Dr. Chen is well known as the originator of the Entity-Relationship Model (ER Model),
which serves as the foundation of many systems analysis and design methodologies,
computer-aided software engineering (CASE) tools, and repository systems. Dr. Chen is
currently a member of several XML working groups that are investigating the linkage
between the hypertext concept and the main ERD concept.
Edgar F. Codd
Contact Information
IBM Research Laboratory
San Jose, California
Research areas
Dr. Codd invented the relational data model in a series of research papers published
commencing in 1970. The relational data model is particularly well suited for business
data management. In this model, data are organized into tables. The data can be
manipulated using a relational algebra. SQL is a standard language for talking to a
relational database. Dr. Codd also introduced the concept and rules of data
normalization.
Won Kim
Contact Information
CEO of Cyber Database Solutions, Inc., Austin, Texas
won.kim@cyberdb.com
Research Areas
Dr. Kim’s research interests lie in object-oriented databases and modern database
systems. He is a founder of UniSQL and recently published a white paper describing a
framework with which to evaluate the completeness of a product's compliance with seven
major categories of capabilities of object relational databases.
Stuart E. Madnick
Contact Information
Address: E53-321
Department: School Of Management
Title: John Norris Maguire Professor of Information Technology
Email: smadnick@MIT.EDU
Phone: (617) 253-6671
URL: http://mit.edu/smadnick/www/home.html
19
Research Areas
Dr. Madnick’s current research interests include connectivity among disparate distributed
information systems, database technology, software project management, and the
strategic use of information technology. He is presently co-director of the PROductivity
From Information Technology (PROFIT) Initiative and co-heads the Total Data Quality
Management (TDQM) research program.
He has been the Principal Investigator of a large-scale DARPA-funded research effort on
Context Interchange which involves the development of technology that helps
organizations to work more cooperatively, coordinated, and collaboratively. As part of
this effort, he is the recent co-inventor on the patent applications "Querying
Heterogeneous Data Sources over a Network Using Context Interchange" and "Data
Extraction from World Wide Web Pages."
He has been active in industry, making significant contributions as a key designer and
developer of projects such as IBM's VM/370 operating system and Lockheed's DIALOG
information retrieval system. He has served as a consultant to many major corporations,
such as IBM, ATandT, and Citicorp. He has also been the founder or co-founder of
several high-tech firms, including Intercomp (acquired by Logicon), Mitrol (acquired by
General Electric's Information Systems Company), and Cambridge Institute for
Information Systems (subsequently re-named Cambridge Technology Group), and
currently operates a hotel in the 14th century Langley Castle in England.
Salvatore T. March
Contact Information
University of Minnesota, Carlson School of Management
3-418 Humphrey Center
(612) 624-2017 smarch@csom.umn.edu
Research Areas
Dr. March’s research interests lie in database design, information system development,
and distributed systems. His current research includes distributed database design and
methodology evaluation.
Sudha Ram
Contact Information
Management Information Systems
College of Business and Public Administration
University of Arizona
ram@bpa.arizona.edu
Research Areas
Dr. Ram's research deals with modeling and analysis of database and knowledge based
systems for manufacturing, scientific and business applications. Her research has been
funded by IBM, NCR, US ARMY, NIST, NSF, NASA, and ORD (CIA). Specifically,
the research deals with interoperability among distributed and heterogeneous database
systems, semantic modeling, data allocation, schema and view integration, intelligent
agents and digital libraries for data management, and automated tools for database
design. E-Business infrastructure and strategy is also one of her favored areas.
20
Joseph S. Valacich
Contact Information
College of Business and Economics
Todd Hall 240D
Washington State University
Pullman, WA 99164-4736
jsv@wsu.edu (509) 335-1112
Research Interests
His current research interests include electronic commerce, the diffusion of technology in
organizations, group decision behavior, and distance learning.
Key Papers
E. F. Codd: A Relational Model of Data for Large Shared Data Banks. CACM 13(6):
377-387 (1970)
Future users of large data banks must be protected from having to know how data is
organized in the computer (the internal representation). Activities of users at terminals
and most application programs should remain unaffected when the internal representation
of data is changed and even when some aspects of the external representation are
changed. Modifications to data representation will often be needed as a result of changes
in query, update, and report traffic and natural growth in the types of stored information.
Peter P. Chen: The Entity-Relationship Model: Toward a Unified View of Data. ACM
Transactions on Database Systems: Vol. 1, Issue 1, Pages 9-36 (1976)
A data model, called the entity-relationship model, is proposed in this model. This model
incorporates some of the important semantic information about the real world. A special
diagrammatic technique is introduced as a tool for database design. An example of
database design and description using the model and the diagrammatic technique is
given. Some implications for data integrity, information retrieval, and data manipulation
are discussed.
Salvatore T. March, M.J. Prietula: Form and Substance in Physical Database Design: An
Empirical Study. Information Systems Research. December 1991
“Data model issues for object-oriented applications”; Jay Banerjee, Hong-Tai Chou,
Jorge F. Garza, Won Kim, Darrell Woelk, Nat Ballou and Hyoung-Joo Kim; ACM Trans.
Inf. Syst. 5, 1 (Jan. 1987), Pages 3 – 26
“Semantics and implementation of schema evolution in object-oriented databases”; Jay
Banerjee, Won Kim, Hyoung-Joo Kim and Henry F. Korth; Proceedings of the ACM
SIGMOD Annual Conference on Management of data, 1987, Pages 311 – 322
“A distributed object-oriented database system supporting shared and private databases”;
Won Kim, Nat Ballou, Jorge F. Garza and Darrell Woelk; ACM Trans. Inf. Syst. 9, 1 (Jan.
1991), Pages 31 – 51
21
"Semantic Model Support for Geographic Information Systems", Sudha Ram with J. Park
and G. Ball. IEEE Computer, Vol. 32, No. 5, May 1999, pp. 74-81.
"Collaborative Conceptual Schema Design: A Process Model and a Prototype Systems",
Sudha Ram with V. Ramesh. ACM Transactions on Information Systems, Vol. 16, No.
4, Oct. 1998, pp. 347-371.
"Database Allocation in a Distributed Environment: Incorporating Concurrency Control
and Queuing Costs", Sudha Ram with S. Narasimhan. Management Science Vol. 40, No.
8, August 1994.
“Metadata Jones and the Tower of Babel: The Challenge of Large-Scale Semantic
Heterogeneity”, Stuart E. Madnick. 1999 IEEE Meta-Data Conference, April 6-7, 1999
“Properties of storage hierarchy systems with multiple page sized and redundant data”;
Chat-Yu Lam and Stuart E. Madnick; ACM Trans. Database Syst. 4, 3 (Sep. 1979), Pages
345 – 367
“Lessons learned from modeling the dynamics of software development”; Tarek K.
Abdel-Hamid and Stuart E. Madnick; Commun. ACM 32, 12 (Dec. 1989), Pages 1426 –
1438
22
E-Commerce
Introduction
Electronic commerce technologies are the fundamental infrastructure for commerce,
communication and communities in the digital age. Basic advancements in engineering
and computer technologies are spawning an astounding array of new applications which
extend the use of computers and networking into all aspects of economic, social and
political activities. While the vision of a networked, digital society is most compelling,
the continuing process of technological developments and applications poses a serious
challenge in defining research priorities that sufficiently address both the emerging vision
of the future and the need to foster and impart basic scientific body of knowledge. The
goal of basic research in electronic commerce is to foster advances in related areas, to
maximize the synergistic, to increase interdisciplinary understanding of how electronic
commerce technologies affect market processes and welfare, and to assure that electronic
commerce applications achieve their promised efficient outcomes.
Key Issues, Conflicts, and Major Research Problems
1. Infrastructure and system architecture area:
Current efforts are focused on developing secure and reliable transaction infrastructure
and pricing regimes. Critical applications being researched and refined include search and
recommendation algorithms that lay the foundation for commercial interactions. The lack
of interoperability in system architecture and application software highlights the need for
net-centric, component-based technologies. The areas for future research initiative focus
on technologies and applications that facilitate real time interactions among users and
computers, including the use of software agents and intermediaries, human-computer
interface design, and system architecture for remote and real-time interactions. In
addition to technology developments, adequate models and measurements must be
developed to be informed about the status, performance and effect of the underlying
system.
2. The interplay between technological infrastructure and commercial environment:
This interplay results in a number of issues that have economic and social ramifications.
For example, the digital online environment has made privacy and intellectual property
rights the most discussed topic in electronic commerce. Nevertheless, current discussions
are carried out in separate circles that focus on technological choices, legalities or other
limited aspects of these issues. It is critical to understand emerging conflicts in a broader,
interrelated solution space and to promote interdisciplinary dialogue and collaboration in
order to provide guidance for design and rule making within the context of online
environment.
23
Key Researchers
Lynda M Applegate
Harvard University
Graduate School of Business Administration
Web site: http://www.people.hbs.edu/lapplegate/research.html
Research areas
Lynda M. Applegate's research focuses on the influence of information technology on
markets and organizations. Her findings on the evolution of electronic commerce and on
the role of information technology as an enabler of flexible and adaptive organizational
designs and innovative management control systems have been widely published in the
Harvard Business Review, Management Systems Quarterly, Organizational Computing,
Information Systems and Decision Processes, and Operations Research, among other
journals. Applegate recently authored a custom-published casebook, Managing in an
Information Age, and co-author of Corporate Information Systems Management: The
Issues Facing Senior Executives.
Andrew B. Whinston
Center for Research in Electronic Commerce
College and Graduate School of Business
University of Texas at Austin
Web site: http://crec.bus.utexas.edu/abw/main.html
Research areas
His current research spans various realms of Electronic Commerce, its impact on
business protocols and processes, on organizational structure and corporate networks,
electronic publishing, electronic education, complementarity of convergent
computational paradigms and business value of IT. Through diverse initiatives, various
aspects and consequences of the emergent economies over the Internet and corporate
Intranets are studied.
Vladimir Zwass
School of Computer Science and Information Systems
Fairleigh Dickinson University
Web site: http://inside.fdu.edu/pt/zwass.html
He is the Editor-in-Chief of the Journal of Management Information Systems, a
leading journal in the field, and of the International Journal of Electronic
Commerce, the first scholarly journal fully devoted to E-commerce.
Tridas Mukhopadhyay
Professor of Industrial Administration
Director, Institute for eCommerce
Carnegie Mellon University
http://www.gsia.cmu.edu/afs/andrew/gsia/
workproc/roster/fulltime/mukhopadhyay.html
Prof. Mukhopadhyay's research centers on the business value of information, EDI
technology, residential use of the Internet and software cost management.
24
Yannis Bakos
Leonard N. Stern School of Business
New York University
Web site: http://www.stern.nyu.edu/~bakos/
Professor Bakos is an internationally acclaimed expert on electronic commerce,
having pioneered research on the impact of information technology on markets,
and in particular on how internet-based electronic marketplaces will affect pricing and
competition. Professor Bakos is also currently studying pricing strategies for information
goods.
Haim Mendelson
Codirector, center for electronic business and commerce
Stanford University
Web site: http://gobi.stanford.edu/facultybios/bio.asp?ID=104
Organizing for e-business, electronic commerce, electronic networks, financial
markets
Key papers
1. Malone, T. W., Yates, J., and Benjamin, R. I. (1987). Electronic Markets and
Electronic Hierarchies. Communications of the ACM, 30(6), 484-497.
By reducing the costs of coordination, information technology will lead to an overall shift
toward proportionately more use of markets-rather than hierarchies-to coordinate
economic activity.
2. Applegate, L. M., Holsapple, C. W., Kalakota, R., Radermacher, F. J., and Whinston,
A. B. (1996). Electronic commerce: building blocks of new business opportunity. Journal
of Organizational Computing and Electronic Commerce, 6(1), 1-10.
There is much uncertainty in the emerging world of electronic commerce. This
uncertainty spans a variety of areas-management, consumer behavior and technology-but
this is good news. History provides numerous examples where market uncertainty has
created potential for shaping new products, creating markets, and building a loyal
customer base. A good case study of uncertainty management is Microsoft, which in the
turbulent days of the early PC software market shaped an entire industry and continues to
reap the benefits. We are on the brink of changes that are projected to rival in impact the
Industrial Revolution of the 18th and 19th Centuries. Much more than making entirely
new knowledge-based products possible, it is clear that electronic commerce will lead to
a fundamental redefinition of the way business is conducted. All participants in the
business community need to wake up to, understand and adapt to electronic commerce.
They need to redefine their business philosophies and approaches so as to position their
organizations to rise with the tide.
3. Vladimir Zwass. Structure and Macro-level impacts of electronic commerce: From
technological infrastructure to electronic marketplaces
25
Electronic commerce (E-commerce) is sharing business information, maintaining
business relationships, and conducting business transactions by means of
telecommunications networks. Traditional E-commerce, conducted with the use of
information technologies centering on electronic data interchange (EDI) over proprietary
value-added networks, is rapidly moving to the Internet. The Internet's World Wide Web
has become the prime driver of contemporary E-commerce. This paper presents a
hierarchical framework of E-commerce, consisting of three meta-levels: infrastructure,
services, and products and structures, which, in turn, consist of seven functional levels.
These levels of E-commerce development, as well as of analysis, range from the widearea telecommunications infrastructure to electronic marketplaces and electronic
4. Frederick J. Riggins and Tridas Mukhopadhyay "Overcoming EDI Adoption and
Implementation Risks," International Journal of Electronic Commerce, Volume 3,
Number 4, Summer 1999,
The emergence of the Internet as a business-to-business communications tool enables a
new wave of adoption of EDI and other interorganizational systems. Initiators of these
trading-partner relationships must develop concrete strategies for managing the adoption
and implementation risks associated with EDI. They may have to subsidize both the
initial adoption and subsequent internal usage of these systems by their trading partners if
they are to maximize their benefits from the technology. EDI can create strategic value in
certain circumstances. To improve internal processes and thus produce operational
benefits, it must improve the information flow between trading partners to the point
where it exceeds the threshold level. Finally, because the operational benefits of EDI are
context-specific, initiators should require their trading partners to develop specific
metrics to measure its effect.
5. Bakos, Y. "A Strategic Analysis of Electronic Marketplaces," MIS Quarterly, Volume
15, No. 3, September 1991, pp. 295-310.
Information systems can serve as intermediaries between the buyers and the sellers in a
vertical market, thus creating an "electronic marketplace". A major impact of these
electronic market systems is that they typically reduce the search costs buyers must pay
to obtain information about the prices and product offerings available in the market.
Economic theory suggests that this reduction in search costs plays a major role in
determining the implications of these systems for market efficiency and competitive
behavior. This article draws on economic models of search and examines how prices,
seller profits, and buyer welfare are affected by reducing search costs in commodity and
differentiated markets. This reduction results in direct efficiency gains from reduced
intermediation costs and in indirect but possibly larger gains in allocational efficiency
from better-informed buyers. Because electronic market systems generally reduce buyers'
search costs, they ultimately increase the efficiency of interorganizational transactions, in
the process affecting the market power of buyers and sellers. The economic
characteristics of electronic markets, in addition to their ability to reduce search costs,
create numerous possibilities for the strategic use of these systems.
26
Group Support System (GSS)
Introduction and Key Theories
Group Support Systems (GSS) are interactive computer-based environments that support
concerted and coordinated team effort toward completion of joint tasks. GSS allow
groups to work in parallel, typically under anonymous conditions; which allows for high
volume and high quality of deliverable output. GSS can radically change the dynamics of
group interactions by improving communication, by structuring and focusing problem
solving efforts, and by establishing and maintaining an alignment between personal and
group goals. GSS has been used to benefit to many group processes such as
brainstorming, idea generation, SAandD, JAD, and process modeling. As a result, GSS
research is a field of great breadth that involves not only technological aspects, but also
facts such as teaming, facilitation, and group dynamics. One important effect of GSS is
its role of increasing intellectual bandwidth. According to Dr. Jay Nunamaker,
information flows into knowledge management systems (KM) and group support systems
(GSS), and these two systems work synergistically to leverage intellectual bandwidth.
Key Issues and Conflicts
Distributed collaboration is viewed as the major issue. A distributed group support
system has to enable both the facilitator and the participants to perform their tasks. The
facilitator needs a way to monitor the interactions in order to control the collaboration
process. The participants also need a means for communicating with the facilitator as
well as other participants. Another key issue for distributed collaboration is whether the
distributed users can develop the level of awareness and trust required for effective
collaboration. Furthermore, connectivity is a key technological issue for the success of
distributed meetings. Connectivity is especially important for the web-based
collaborations because of the heterogeneity of distributed sites.
Major Research Problems in the Future
The following are key issues and research problems need to be addressed:(this part is
summarized from the article Lessons from a Dozen Years of Group Support Systems
Research: A Discussion of Lab and Field Findings, please see key paper 3 for more
information)
GSS research of distributed groups across different geographical areas (including
distributed facilitation research);
Research of integration of GSS with video conferencing;
Research of integration of GSS with automatic language translation to support
multilingual groups;
Research of GSS transfer and adoption in cultures other than English-speaking countries;
research of GSS to support heterogeneous group; sophisticated GSS software to support
group communication and writing;
Possible uses of GSS in the classroom
27
Key Researchers
Jerry DeSanctis
Fuqua School of Business, Duke University
Awards
Outstanding teacher award, Texas Tech University, 1980
Award for Distinguished Contributed Paper in MIS at the National meeting of
the American Institute for Decision Sciences, 1983
Top Three paper at the Annual Meeting of the International Communication Association,
Human Communication Technology Interest Group, May 1988 (with R. Watson and M.
S. Poole)
Invited member of the doctoral consortium faculty, International Conference on
Information Systems, December 1988
Top Three paper in the Annual Meeting of the International Communication Association,
Human Communication Technology Interest Group, May 1989 (with M.S. Poole)
Invited Chair of the Doctoral Consortium, Thirteenth International Conference on
Information Systems, 1992
Received Best Paper Award, 24th Annual Hawaii International Conference on System
Sciences Collaboration Technology Track, "Using Computing to Improve the Quality
Team Process: Preliminary Observations from the IRS-Minnesota Project," 1991
Current Research
Organizational computing, computer-supported cooperative work and management of
information systems
R. Brent Gallupe
Queens University, School of Business
Current Research
Electronic brainstorming, the history of information systems, E-commerce
management issues, Knowledge management systems, Evaluation of information
systems.
Sara Kiesler
Carnegie Mellon University
Current Research
The social and behavioral aspects of computers and computer-based communication
technologies, the emotional and social effects of computing technology on individuals,
teams, and families; (detailed research areas include: influence of computer networking
on group dynamics and communication in organizations, the research of the causes of
"flaming", the conditions for social equalization on computer networks, the benefits and
costs of open communication on networks, the illusion of electronic privacy, the uses and
misuses of electronic surveys, the formation and conduct of electronic groups,
information sharing on networks, and the impact of computer communication on
peripheral or marginal organizational groups). Current projects: investigations of
household technologies and e-commerce, an NSF-sponsored study on interdisciplinary
collaboration; HomeNet, a field study of families using the Internet
28
Key paper
Galagher, J., Sproull, L., and Kiesler, S. (1998). Legitimacy, authority, and community
in electronic support groups. Written Communication, 15, 493-530.
Jay F. Nunamaker, Jr.
Center for the Management of Information, University of Arizona
Awards
Regents Professor / Soldwedel Chair, 1994 - Present.
Received the DPMA EDSIG Distinguished IS Educator Award.
GroupSystems software received the Editor's Choice Award from PC Magazine, June 14,
1994.
GroupWare Achievement Award, GroupWare Conference, San Jose, 1993
GroupSystems: best of show in the GDSS category, GroupWare Conference, San Jose,
1993.
Arthur Andersen Consulting Professor of the Year Award, 1992
Professional Activity
Editorial board of six journals.
Chairman, ACM Curriculum Committee on Information Systems, 1976-1991.
Track Chairman, Data and Knowledge Bases, Decision Support Systems and Information
Systems, Hawaii Conference 1990 - 1997.
Founding member of International Conference on Information Systems, 1980.
Served on Faculty at AACSB Basic and Advanced Institutes for faculty retraining, 198391.
Current Research
Computer supported collaboration and decision support to improve productivity and
communication.
Wanda J. Orlikowski
MIT Sloan School of Management
Current Research
Organizational changes associated with the use of information technology; the
ongoing relationship between information technologies and organizing
structures, work practices, communication, culture, and control mechanisms;
the use of groupware technologies in organizations; the social and technological aspects
of working virtually.
Key paper
“The Duality of Technology: Rethinking the Concept of Technology in Organizations”,
Organization Science, vol. 3, no. 3, August 1992: 398-427.
Judy Olson
School of Information, University of Michigan
Awards
Amoco Award for Outstanding Teaching, 1980
Administrative Internship, University of Michigan, Office of the President,
1980
Council: Association for Computing Machinery
29
National Research Council Committee on Human Factors, 1982-89
Professional Activity
Editorial Board: Journal of Experimental Psychology: Applied, 1994-present
Editorial Board: Management of Information Systems Quarterly, 1990-94
Editorial Board: Organizational Computing, 1990-present
Editorial Board: Human Computer Interaction, 1982-present
Editorial Board: Psychological Review, 1980-82
Editorial Board: Memory and Cognition, 1977-78
Current Research
Collaboration technology, Human-computer interaction, software design process
Applications of cognitive psychology to business computing and communication
Key paper
"Group Work Close Up: A Comparison of the Group Design Process With and Without a
Simple Group Editor" (with G. M. Olson, M. Storrsten and M. Carter). ACM:
Transactions on Information Systems, 1993.
Sirkaa L. Jarvenpaa
McCombs School of Business, University of Texas at Austin
Awards
Distinguished Visiting Scholar, University of Melbourne, Australia, 1997
Harvard Business School Grant, 1995
The Center for International Business and Education Grant, 1995
Current Research
Clicks and mortars, customer insight, e-commerce, information systems, communication
and trust in global virtual teams
Key Paper
"Is Anybody Out There?: The Antecedents of Trust in Global Virtual Teams," (with K.
Knoll and D. Leidner), Journal of Management Information Systems, 1998
Douglas R. Vogel
Department of Information Systems, City University of Hong Kong
Current Research
Group support systems, business process improvement, executive support
systems, technology support for learning environments, electronic commerce,
virtual organization
Key Paper
Vogel, D. and Nunamaker, J., "Group Decision Support System Impact: MultiMethodological Exploration", Information and Management (1990), 15-28.
Key Papers
1. DeSanctis, G., and Gallupe, R. B. (1987). A Foundation for the Study of Group
Decision Support Systems. Management Science, 33(5), 589-609.
The paper identifies the need of GDSS research, and presents a conceptual overview of
GDSS based on an information-exchange perspective of decision-making. Three levels of
systems are described, representing varying degrees of intervention into the decision
30
process. The paper describes the evolution of GDSS. A multidimensional taxonomy of
systems is proposed as an organizing framework for research in the area. The paper also
identifies three critical environmental contingencies to GDSS design: group size, member
proximity, and the task confronting the group. Potential impacts of GDSS on group
processes and outcomes are discussed, and important constructs in need of study are
identified.
2. Gallupe, R. B., Dennis, A. R., Cooper, W. H., Valacich, J. S., Bastianutti, L. M., and
Nunamaker, J. F. (1992). Electronic Brainstorming and Group Size. Academy of
Management Journal, 35(2), 350-369.
This article summarizes research to determine whether or not group size has an effect on
electronic brainstorming by using different group size. The authors found that larger
groups using GSS indeed generated more, high-quality ideas and experienced higher
levels of satisfaction than groups that did not use technology. However, in small groups
(e.g. 2 group members) technology did not act as a catalyst for higher productivity;
primarily because there was no anonymity and not much production blocking (two
primary reasons larger GSS group succeeded).
3. Nunamaker, J. F., Briggs, R. O., Mittleman, D. D., Vogel, D. R., and Balthazard, P. A.
(1997). Lessons from a Dozen Years of Group Support Systems Research: A Discussion
of Lab and Field Findings. Journal of Management Information Systems, 13(3), 163-207.
The paper presents an overview of GSS research conducted in University of Arizona,
where researchers have built 6 generations of group support systems software, conducted
over 150 research studies and facilitated over 4,000 projects. The paper reports research
results and lessons learned from the studies. The paper also proposes Groupware Grid,
which is a theory-based heuristic model for evaluating the contributions of groupware
technology to team productivity. Research results and lessons are presented from 9 key
areas: 1. GSS in organizations, 2. cross-cultural and multicultural issues, 3. designing
GSS software, 4. collaborative writing, 5. electronic polling, 6. GSS facilities and room
design, 7. leadership and facilitation, 8. GSS in classroom, and 9. business process
reengineering.
4. Nunamaker, J. F., Dennis, A. R., Valacich, J. S., Vogel, D. R., and George, J. F.
(1991). Electronic Meeting Systems to Support Group Work. Communications of the
ACM, 34(7), 40-61.
This is a "classic" GSS article written by Dr. Nunamaker, et al. This is one of the
fundamental, early guides to GSS. The article explains the group losses and gains of a
group meeting, discusses the potential benefits of using GSS by increasing group gains
and decreasing group losses. GSS utilizes four mechanisms to support a meeting: process
support, process structure, task support, and task structure. The paper also discusses the
specific implementation of GSS through GroupSystems, a GSS software developed at the
University of Arizona. Three facilitation styles are discussed, and how GSS strongly
supports an integrative facilitation style is illustrated.
31
5. Fjermestad, J., and Hiltz, S. T. (1999). An assessment of Group Support Systems
Experimental Research: Methodology and Results. Journal of Management Information
Systems, Vol. 15 No. 3, Winter 1999 7-150
This landmark paper summarizes the methods and results of the whole area of
experimental GSS studies published in the English language in referred academic
journals. The paper specifically excludes case studies from the field, focusing on
analyzing experimental results. The paper presents an exhaustive list of authors, editors,
reviewers, and major GSS researchers at press time. In addition to the exhaustive
bibliography, the authors offer clear, readable tables summarizing each experiment, and
detailing research methods, hypotheses, and results for 200 experiments. The authors also
offer a classification scheme for the dependent and independent variables in these
experiments, examining which are initial causes, which are intervening variables, and
which are outcome variables. This paper can serve as an outstanding pedagogical
resource for courses in MIS research and research methodologies.
6. Nunamaker, J. F., Chen, M., and Purdin, T.D.M. Systems Development in Information
Systems Research. Journal of Management Information Systems, Vol. 7, No.3, Winter
1990-1991, 89-106
The paper discusses the methodology of MIS research such as theory building,
experimentation, observation and system development. The contribution of the paper is
that it discusses the validity of MIS research as a research domain and proposes system
development as a valid and critical research methodology in MIS. The paper illustrates
MIS research is multimethodological and multidimensional, integration of system
development and traditional research methodology can lead to fruitful MIS research.
32
Information Economics
Key Issues and Conflicts
The interdisciplinary research of information economics draws on principles of
information science, economics, management, political science, public policy,
organizational theory, psychology, ethics, and computer science to propose answers to
the tough new questions confronting the networked society:
When does sharing proprietary information improve a firm’s competitive stance?
Does information technology encourage or impede information equality?
When does it make economic sense to give away information products for free?
Does the Internet require a new regulatory paradigm?
What business models work for information commerce, and how should information
goods be priced [1]?
Most Important Theories
Information asymmetry
Bayes, decision theory, and choice
Principal-agent models
Moral hazard
Adverse selection
Revelation mechanisms
Concepts of information
Shannon entropy
Turing machine (instructional/computational)
Information pricing
Value
Hedonics
Options
Packaging information
Macroeconomic effects
Growth theory
Information markets
Intellectual property
Creation incentives vs. monopoly costs
Patents and copyrights
Information and social policy [2]
References:
[1] University of Michigan School of Information,
http://www.si.umich.edu/academics/iemp/
[2] University of Michigan School of Information,
http://www.si.umich.edu/Classes/646/#itopics
33
Key Researchers
Erik Brynjolfsson
Massachusetts Institute of Technology
Email: erikb@mit.edu
Webpage: ebusiness.mit.edu/erik
Research area: Information technologies and productivity, Internet implications
for pricing, organizational change
Charles H. Kriebel
Carnegie Mellon University
Email: ck04@andrew.cmu.edu
Research area: Computers and information systems, information economics,
telecommunications, management science, operations management, robotics,
applied economics, productivity, manufacturing systems, information resource
management.
Tridas Mukhopadhyay
Carnegie Mellon University
Email: tridas@andrew.cmu.edu
Research area: Business value of information technologies, business-to-business
commerce, residential use of the Internet, software cost management.
Andrew B. Whinston
University of Texas at Austin
Email: abw@uts.cc.utexas.edu
Webpage: cism.bus.utexas.edu
Research area: Artificial intelligence, e-commerce, information systems, the new
economy
Key papers
Masuda Y. “Conceptual Framework Of Information Economics.” IEEE-Transactions-onCommunications, October 1975, 23: (10) 1028-1040.
Information economics is a new system of economics, overriding the classical school of
economics, and at the same time it is a future economics. Three basic concepts of
economics constitute the framework of information economics. The first of them is the
spirit of globalism-the ideas of spaceship, quality of time, and coexistentialism. The
second is information productivity. The development of computer and communication
technologies has made possible mass production of objective-oriented, logical, normative
information. The third is time value-a new view of values. By time value is meant the
value that is created through objective-oriented utilization of free time at the disposal of
human beings. Just as each new theory of economics has a new vision, information
economics has a vision-Global Futualization Society as the society where a large variety
34
of voluntary communities will flourish on a global scale at a time, and the individual will
seek to realize self-acturalization in each community.
Barua, A., Kriebel, C.H., Mukhopadhyay, T. “An Economic Analysis of Strategic
Information Technology Investments.” MIS Quarterly, September 1991, Vol. 15, Iss. 3,
313-332.
The strategic impacts of information technology (IT) investment are studied through the
development of a formal economic model. In particular, the study focuses on IT-related
quality competition in a duopoly, where the services may not be priced initially and
where the benefits may come indirectly. A firm may have to invest in IT, regardless of its
underlying cost structure, as a response to its competitor's investment level. Both firms
prefer sequential over simultaneous investments, even when both have the required
technology. While the IT-inefficient firm has followership incentives, the leadership
incentives for the IT-efficient firm depend on the difference in IT cost structures and on
the degree of substitutability between the services of the 2 firms. For dynamic markets
with new consumers, the negative effect of switching cost on the welfare of existing
consumers is reduced when the IT-efficient firm moves first.
Clemons E., Kleindorfer P. “An Economic-Analysis Of Interorganizational Information
Technology.” Decision Support System, September 1992, 8: (5) 431-446.
This paper first reviews some basic results on the economics of information technology
(IT) and strategy. These results begin by developing a model of interorganizational IT,
focusing on supplier-buyer interactions and the costs and benefits of IT in facilitating
such interactions. The modeling framework incorporates economies of scale and scope,
transactions specific sunk costs of IT development, and related issues of bargaining and
opportunism. Results of the model are applied to the increasingly important topic of
interorganizational information systems, addressing some of the risks of cooperative
ventures that are frequently overlooked in the MIS literature.
Kriebel C., Barua A. and Mukhopadhyay T. “Information Technologies and Business
Value: An Analytical and Empirical Investigation.” Information Systems Research,
March 1995, Vol. 6, Iss. 1, 3-24.
An important management question today is whether the anticipated economic benefits of
information technology (IT) are being realized. In an analysis, this problem is considered
to be measurement related, and a new process-oriented methodology for ex post
measurement is proposed and tested to audit IT impacts on a strategic business unit
(SBU) or profit center's performance. The IT impacts on a given SBU are measured
relative to a group of SBUs in the industry. The methodology involves a 2-stage analysis
of intermediate and higher level output variables that also accounts for industry and
economy wide exogenous variables for tracing and measuring IT contributions. The data
for testing the proposed model were obtained from SBUs in the manufacturing sector.
The results show significant positive impacts of IT at the intermediate level. The study
provides a practical management tool to address the question of why (or why not) certain
IT impacts occur.
35
Nadiminti R., Mukhopadhyay T., Kriebel C.H. “Risk aversion and the value of
information.” Decision Support System, March 1996,16: (3) 241-254.
Determining the value of information is a fundamental research problem for information
system scientists. Unfortunately, very little research exists that examines the relationship
between risk aversion and the value of information. This is surprising because empirical
studies show that most managers are risk averse rather than risk neutral. Moreover, the
small literature that exists appears to be in conflict. We have developed a framework to
examine the relationship between the value of information and risk aversion. We show
that the method of payment for information must be considered in determining this
relationship. We have used the Arrow-Pratt measure of risk aversion to derive explicit
conditions under which the value of information increases (decreases) with risk aversion.
From our analysis it is clear that earlier work has depicted a limited view of the
relationship between risk aversion and value of information. Our analysis is applicable to
the ex-post evaluation of transaction processing systems and a subset of decision and
expert support systems.
Brynjolfsson, E. and Hitt, L. “Paradox Lost? Firm-level Evidence on the Returns to
Information Systems Spending.” Management Science, April 1996.
The "productivity paradox" of information systems (IS) is that, despite enormous
improvements in the underlying technology, the benefits of IS spending have not been
found in aggregate output statistics. One explanation is that IS spending may lead to
increases in product quality or variety which tend to be overlooked in aggregate output
statistics, even if they increase sales at the firm-level. Furthermore, the restructuring and
cost-cutting that are often necessary to realize the potential benefits of IS have only
recently been undertaken in many firms. Our study uses new firm-level data on several
components of IS spending for 1987-1991. Our results indicate that IS have made a
substantial and statistically significant contribution to firm output.
Hitt, L. and Brynjolfsson, E. “Productivity, Profit and Consumer Welfare: Three
Different Measures of Information Technology's Value.” MIS Quarterly, June 1996.
The business value of information technology (IT) has been debated for a number of
years. While some authors have attributed large productivity improvements and
substantial consumer benefits to IT, others report that IT has not had any bottom line
impact on business profitability. In this paper, we focus on the fact that while
productivity, consumer value and business profitability are related, they are ultimately
separate questions. Accordingly, the empirical results on IT value depend heavily on
which question is being addressed and what data are being used. Applying methods based
on economic theory, we are able to define and examine the relevant hypotheses for each
of these three questions, using recent firm-level data on IT spending by 370 large firms.
Our findings indicate that IT has increased productivity and created substantial value for
consumers. However, these benefits have not resulted in supernormal business
profitability. We conclude that while modeling techniques need to be improved, these
results are consistent with economic theory. Thus, there is no inherent contradiction
between increased productivity, increased consumer value and unchanged business
profitability.
36
Brynjolfsson, E. “The contribution of information technology to consumer welfare.”
Information Systems Research, September 1996 Vol. 7, Iss. 3 pg. 281, 20 pgs.
Over the past 2 decades, US businesses have invested heavily in information technology
(IT) hardware. Managers often buy IT to enhance customer value in ways that are poorly
measured by conventional output statistics. Further, because of competition, firms may be
unable to capture the full benefits of the value they create. This undermines researchers'
attempts to determine IT value by estimating its contribution to industry productivity or
to company profits and revenues. An alternative approach estimates the consumers'
surplus from IT investments by integrating the area under the demand curve for IT. Using
data from the US Bureau of Economic Analysis, 4 measures of consumers' surplus are
estimated: 1. Marshallian surplus, 2. Exact surplus based on compensated (Hicksian)
demand curves, 3. a nonparametric estimate, and 4. a value based on the theory of index
numbers. All 4 estimates indicate that in the base year of 1987, IT spending generated
approximately $50 billion to $70 billion in net value in the US and increased economic
growth by about 0.3% per year. According to conservative estimates, IT investments
generate approximately 3 times their cost in value for consumers.
37
Information Retrieval
Key Issues
The techniques used in information retrieval are as follows:
(1) Automatic Text Analysis - concerns how the text of a document is represented inside a
computer.
(2) Automatic Classification - looks at automatic classification methods.
(3) File Structures - from the point of view of someone primarily interested in
information retrieval.
(4) Search Strategies - search strategies when applied to document collections structured
in different ways.
(5) Probabilistic Retrieval - a formal model for enhancing retrieval effectiveness by using
sample information about the frequency of occurrence and co-occurrence of index terms
in the relevant and non-relevant documents.
Trends
(1).
(2).
(3).
(4).
(5).
(6).
Multimedia Information Retrieval
Collaborative Information Retrieval
Multilingual Information Retrieval
Semantic Web (linked concept)
Text Mining, Web Mining
Mobile /Wireless Computing
Key People
Gerard Salton
Description
Professor, Computer Science at Cornell University.
Founder of Information Retrieval, died of cancer on 28 August, in Ithaca,
NY (1927-1995). ACM Award for Outstanding Contributions in 1983 (The
first such award was given to G. Salton)
Research Interests
Natural language processing, information retrieval
Karen Sparck Jones
Description
Computer Laboratory, University of Cambridge
Interests
She has worked in automatic language and information processing research since the late
fifties, beginning her career at the then Cambridge Language Research Unit. She has
many publications including several books. Her work in the last decade has been on
document retrieval including speech applications, database query, user and agent
modeling, summarizing, and information and language system evaluation.
38
Gary Marchionini
Description
Current Position: Professor, College of Library and Information Services
Research Interests
Information seeking, human-computer interaction, digital libraries,
information design, information policy.
Edward A. Fox
Description
Professor, Computer Science, Virginia Polytechnic Institute and State
University.
Research Interests
Multimedia information storage and retrieval; digital libraries;
hypertext/hypermedia; electronic publishing and text processing;
educational technology and distance learning; library automation;
artificial intelligence.
W. Bruce Croft
Description
Professor, Department of Computer Science at the University of Massachusetts, Amherst.
Research Interests
His research interests are in formal models of retrieval for complex, text-based objects,
text representation techniques, the design and implementation of text retrieval and routing
systems, and user interfaces. He has published more than 100 articles on these subjects.
This research is also being used in a number of operational retrieval systems.
Key Papers
Automatic Text Structuring and Summarization. Gerard Salton, Amit Singhal, Mandar
Mitra, Chris Buckley: Information Processing and Management 33(2): 193-207 (1997)
In recent years, information retrieval techniques have been used for automatic generation
of semantic hypertext links. This study applies the ideas from the automatic link
generation research to attack another important problem in text processing - automatic
text summarization. An automatic 'general purpose' text summarization tool would be of
immense utility in this age of information overload. Using the techniques used (by most
automatic hypertext link generation link algorithms) for inter-document link generation,
we generate intra-document links between passages of a document. Based on the intradocument linkage pattern of a text, we characterize the structure of the text. We apply the
knowledge of text structure to do automatic text summarization by passage extraction.
We evaluate a set of fifty summaries generated using our techniques by comparing them
to paragraph extracts constructed by humans. The automatic summarization methods
39
perform well, especially in view of the fact that the summaries generated by two humans
for the same article are surprisingly dissimilar.
Automatic Construction of Networks of Concepts Characterizing Document Databases,
Chen, H., and Lynch, K. J. (1992).. Paper presented at the IEEE Transactions on
Systems, Man, and Cybernetics.
We report results of a study that involved the creation of knowledge bases of concepts
from large, operational textual databases. Two East-bloc computing knowledge bases,
both based on a semantic network structure, were created automatically using two
statistical algorithms. With the help of four East-bloc computing experts, we evaluated
the two knowledge bases in detail in a concept-association experiment based on recall
and recognition tests. In our experiment, one of the knowledge bases that exhibited the
asymmetric link property out-performed all four experts in recalling relevant concepts in
East-bloc computing. The knowledge base, which contained about 20,000 concepts
(nodes) and 280,000 weighted relationships (links), was incorporated as a thesaurus-like
component into an.
(12 citations)
Interfaces and tools for the Library of Congress National Digital Library,
Program.Marchionini, G., Plaisant, C., and Komlodi, A. (1998). Information Processing
and Management, 34(5), 535-555.
This paper describes a collaborative effort to explore user needs in a digital library,
develop interface prototypes for a digital library and suggest and prototype tools for
digital librarians and users at the Library of Congress (LC). Interfaces were guided by an
assessment of user needs and aimed to maximize interaction with primary resources and
support both browsing and analytical search strategies. Tools to aid users and librarians in
overviewing collections, previewing objects and gathering results were created and serve
as the beginnings of a digital librarian toolkit. The design process and results are
described and suggestions for future work are offered.
(2 citations)
Theory of term importance in automatic text analysis. Salton, G., Yang, C., and Yu, C.
(1975). Journal Am. Soc. Inform. Sci., 26(1), 33-44.
Evaluating natural language processing systems, Karen Sparck Jones, J.R. Galliers ,
springer, 1996.
This report presents a detailed analysis and review of NLP evaluation, in principle and in
practice. Part 1 examines evaluation concepts and establishes a framework for NLP
system evaluation. This makes use of experience in the related area of information
retrieval and the analysis also refers to evaluation in speech processing. Part 2 surveys
significant evaluation work done so far, for instance in machine translation, and discusses
the particular problems of generic system evaluation. The conclusion is that evaluation
strategies and techniques for NLP need much more development, in particular to take
proper account of the influence of system tasks and settings. Part 3 develops a general
approach to NLP evaluation, aimed at methodologically sound strategies for test and
evaluation.
40
Knowledge Management
Introduction
As the attention of human beings becomes the most critical resource in the information
age, the need to manage vast amount and different levels of knowledge (see Figure 1)
becomes apparent. Knowledge management is a discipline that promotes an integrated
approach to identifying, capturing, retrieving, sharing and evaluating an enterprise’s
information assets. These information assets may include databases, documents, policies
and procedures as well as the un-captured, tacit expertise and experience resident in
individual workers.
KMS Understanding Hierarchy
Context
Wisdom
Principles
High
Knowledge
Patterns
Information
Relations
Low
Data
Symbols
Noise Detection
Easy
Difficult
Figure 1. KMS Understanding Hierarchy
Categories of Knowledge Management Research
Knowledge management investigates areas such as visualization, categorization,
representation of data, information, knowledge and wisdom to enable transfer and sharing
of knowledge and information to other groups and people. This discipline is essentially
divided into technical aspect and behavioral aspect. The technical aspect is composed of
four categories, namely, information retrieval, digital library, collaboration, and data
mining. The behavioral aspect is composed of four categories, namely, consulting in
knowledge management, best practices, organizational memory, knowledge networking /
integration.
41
Key Theories and Methodologies
Knowledge Management is a cross-disciplinary research area. The key theories and
methodologies in the behavioral side include cognitive psychology theories, human
communication theories, and group theories. The key theories and methodologies in the
technical side include statistical theories, self-organizing map, mathematical
representation schemes, automatic text processing methods, workflow technologies,
agent theory, ontology, meta-data and various visualization techniques.
Key Issues
The technical aspect of knowledge management is concerned with how to capture
semantic knowledge and meanings, how to visualize knowledge, how to integrate
knowledge, and how to deal with multilingual knowledge. The behavioral aspect of
knowledge management is concerned with what are the best practices, organizational
change and reward, case studies in knowledge management, and social and human aspect
of knowledge management. The technical and behavioral aspects drive each other to
enhance the field of knowledge management.
Future Research Trends
Relevance -- having all the available, relevant knowledge available for decision-making.
Dynamism -- knowledge about the state of multiple processes operating in parallel and
affecting each other in a coordinated way.
Community -- a collective environment that actively supports sharing through automatic
capture in sharable form and explicit policies and open cultures that promote sharing.
Key Researchers
Christine L. Borgman
Contact Information
Department of Information Studies
Graduate School of Education and Information Studies
University of California, Los Angeles
http://dlis.gseis.ucla.edu/cborgman/
Research Areas
Her research interests include digital libraries, human-computer interaction, information
seeking behavior, and scholarly communication and bibliometrics, as well as information
technology policy in Central and Eastern Europe.
Hsinchun Chen
Contact Information
MIS Department, McClelland Hall 430Z
Karl Eller Graduate School of Management
University of Arizona
http://ai.bpa.arizona.edu/html/faculty.html
42
Research areas
Professor Chen’s research interests include digital library, intelligent information
retrieval, automatic categorization and classification, concept space generation, automatic
thesaurus browsing and traversal, inductive query by examples, machine learning for IR,
large-scale information analysis and visualization, internet resource discovery,
multilingual IR, collaborative systems, intelligence systems.
W. Bruce Croft
Contact Information
Director, Center for Intelligent Information Retrieval
Department of Computer Science
University of Massachusetts, Amherst
http://www.cs.umass.edu/faculty-bios/croft.html
Research Areas
Professor Croft's research interests are in formal models of retrieval for complex, textbased objects, text representation techniques, the design and implementation of text
retrieval and routing systems, and user interfaces. He has published more than 100
articles on these subjects. This research is also being used in a number of operational
retrieval systems.
Daniel E. O'Leary
Contact Information
School of Business
University of Southern California
http://www.usc.edu/schools/business/atisp/oleary.html
Research areas
His current research examines issues in the areas of Electronic
Commerce, Enterprise Resource Planning Systems, Knowledge Management,
Reengineering and Workflow, and Virtual Organizations. His research employs a number
of methodologies, including analytic, artificial intelligence/expert systems, empirical and
case studies.
Gerard Salton
He was (1927-1995) one of the first programmers for the Harvard Mark
IV computer. The “Father” of Information Retrieval.
Research areas
His research interests are natural language processing and information
retrieval. He began the SMART information retrieval system in the
1960's (allegedly, SMART is known as "Salton's Magical Automatic
Retriever of Text"), and ideas in this work fundamentally changed fulltext processing methods on computers and provided the field of information retrieval
with solid underpinnings.
Key Articles
43
Chen, H.; Houston, A.L.; Sewell, R.R.; Schatz, B.R. (1998) “Internet browsing and
searching: User evaluations of category map and concept space techniques,” Journal of
the American Society for Information Science 49(7), pp.582-603.
The development and refinement of algorithms to improve browsing and searching by
addressing information overload and vocabulary differences are discussed. Whether 2
particular algorithms can help improve browsing and searching the Internet is studied.
The results indicate that a Kohenen self-organizing map-based algorithm can successfully
categorize a large and eclectic Internet information space into manageable sub-spaces
that users can successfully navigate to locate a homepage of interest to them. A study of
an automatically generated concept space algorithm for searching was especially
encouraging. Subjects especially like the level of control they could exert over such a
search.
Salton G. Automatic Text Processing, Addison-Wesley Publishing Company, 1989.
This book deals with the whole area of automatic text processing – that is, the handling of
texts using automatic equipment. The aim is not to teach laymen or humanists how to
program computers to manipulate text, nor to teach scientists language-processing skills.
Instead, this book examines the area of text processing as a whole, describing various
text-processing methodologies and identifying those tasks now undertaken routinely,
while also discussing more experimental procedures not yet ready for operation. This
book is divided into four parts: the first part covers the computer environment and
automated office situation, in which text processing is of particular interest. The second
part covers the main word processing areas, which treat texts on the level of individual
words. The third part covers text-retrieval systems whose operations are normally based
on text units larger than single, individual word forms. The fourth part covers the main
language-analysis and language-processing topics in which text meaning and text
understanding are of principle concern: syntactic and semantic language-analysis
methods that determine language structure and text content, and knowledge-based text
processing.
O'Leary, D.E. “Knowledge-Management Systems: Converting and Connecting”, IEEE
Intelligent Systems and their applications 13(3), May-June 1998, pp.30 –33.
Organizations use knowledge management for a number of reasons, including
environmental pressures, technological advancements, and the ability to create valuable
information. Classic knowledge management thinking assumes that a firm gathers all its
important knowledge in a single place, and employees use it to make good decisions that
will benefit the organization. But this classical thinking is only partially right. The full
range of knowledge management converting and connecting capabilities should include
not only connecting knowledge and people, but also link knowledge to other knowledge
or push knowledge to other knowledge or push knowledge out to employees.
Croft, W.B. “Effective text retrieval based on combining evidence from the corpus and
users,” IEEE Expert 10(6), Dec. 1995, pp.59 –63.
The author surveys the representation, query processing and retrieval techniques used in
the Inquiry system. By combining evidence about relevance from the corpus, individual
44
documents and users, Inquiry achieves effective overall recall and precision evaluation
while avoiding occasional major failures.
45
Operation Research
Introduction
Operation Research (OR) looks at an organization’s operations - the functions it exists to
perform. The objective of Operational Researchers is to work with clients to find
practical and pragmatic solutions to operational or strategic problems, often working
within tight timing constraints.
Organizations may seek a very wide range of operational improvements - for example,
greater efficiency, better customer service, higher quality or lower cost. Whatever the
business engineering aim, OR can offer the flexibility and adaptability to provide
objective help.
Most of the problems OR tackles are messy and complex, often entailing considerable
uncertainty. OR can use advanced quantitative methods, modelling, problem structuring,
simulation and other analytical techniques to examine assumptions, facilitate an in -depth
understanding and decide on practical action.
The future issues will focus on decision analysis, vehicle routing, and effectiveness of
mandatory minimum sentencing and information technology. MIS researcher can look at
the opportunities of facilitating OR with information system, making the switch from
academia to the "real world"
Key People
Hau L. Lee
Stanford University
Hau.Lee@stanford.edu
Supply chain management; Global logistic system design and control;
Multi-echelon inventory systems; Manufacturing and distribution
strategy; Design for supply chain management
Marshall Fisher
The University of Pennsylvania
Lanchester Prize, Management Science, 1977
Supply chain management, retailing
46
James B. Orlin
MIT
jorlin@mit.edu, http://web.mit.edu/jorlin/www/
Mathematical Programming, Combinatorial and Network Optimization,
Design and Analysis of Algorithms and Heuristics, Logistics.
George Nemhauser
george.nemhauser@isye.gatech.edu
School of Industrial and Systems Engineering
Georgia Tech
Lanchester prize (twice)
Discrete optimization, solving large-scale mixed-integer programming
problems, crew and fleet scheduling problems in the airline industry.
Ellis Johnson
School of Industrial and Systems Engineering,
Georgia Tech
ellis.johnson@isye.gatech.edu
Lanchester Prize 1983
Mathematical programming and integer programming; theories on
computational approaches; applications in manufacturing, distribution,
and transportation.
Paul H. Zipkin
Fuqua School of Business,
Duke University
PaulZipkin@Duke.Edu
Operations Management; Inventory Management; Supply-chain
Management and Analysis; Product variety; design of logistics networks
Moshe Dror
The University of Arizona
mdror@bpa.arizona.edu
Combinatorial Optimization in Logistics and Manufacturing Systems;
Cooperative Game Theory and Cost Allocation in Inventory and
Combinatorial Problems; Agent Theory and Applications in Operations
Management.
Key Papers
47
Jack Edmonds, “Maximum matching and a polyhedron with 0,1-variation”, Journal of
Research of national Bureau of Standards, 69 (1965), 123-130
Jack Edmonds, “Paths, Trees, and Flowers”, Canadian Jornal of Mathematics, 1965
Thomas L. Saaty, and Chen, Kun Yuan, Hoover's problem. Math. Mag. 51 (1978) 288292 05C20
Ellis Johnson, Manfred Padberg, and Harlan Crowder", Solving Large-Scale Zero-One
Linear Programming Problems" Operations Research, 31:5 (1983), pp. 803-834.
Hau L. Lee, Material Management in Decentralized Supply Chains, Operations
Research, vol. 41 1993
Hau L. Lee, Hau. Information distortion in a Supply Chain: The Bullwhip Effect,
Management Science, 43, 4 1997
James Orlin and Rina R. Schneur, A Scaling Algorithm for Multicommodity Flow
Problems" Operations Research 46, (1998), 231-246.
Dror, M. and Trudeau, P., (1989). "Savings by Split Delivery Routing", Transportation
Science 23, 141-145
Dror, M., Stern, H.I., and Lenstra, J.K., (1987). "Parallel Machine Scheduling:
Production Rates Dependent on Number of Jobs in Operation", Management Science 33,
1001-1009
Cachon, G. and M. Lariviere. 1999. An Equilibrium Analysis of Linear and Proportional
Allocation of Scarce Capacity. IIE Transactions. 31 (9) 835-850.
Cachon, G. and M. Lariviere. 1999. Capacity Choice and Allocation: Strategic Behavior
and Supply Chain Performance. Management Science. 45 (8) 1091-1108.
Glasserman P Introduction to the special issue on stochastic models and simulation
MANAGE SCI 46: (9) III-IV SEP 2000
Glasserman P, Wang YS Leadtime-inventory trade-offs in assemble-to-order systems
OPER RES 46: (6) 858-871 NOV-DEC 1998
Masuda Y, Whang S Dynamic pricing for network service: Equilibrium and stability
MANAGE SCI 45: (6) 857-869 JUN 1999
Barnett A.l., Comment on a Market Share Theorem-comment, J Marketing Research, 13:
(3) 312-312 1976
Zipkin P. H., Performance Analysis of a Multiitem Production-Inventory System Under
Alternative Policies, Manage Sci. 41: (4) 690-703 APR 1995
48
Zipkin P.H. Computing Optimal Lot Sizes in the Economic Lot Scheduling Problem,
Operation Research, 39: (1) 56-63 JAN-FEB 1991
Kelton W.D., Random Initialization methods in Simulation, IIE TRANS 21: (4) 355-367
DEC 1989
Chen, F. Optimal Policies for Multi-Echelon Inventory Problems with Batch Ordering.
Operations Research 48, 376-389. 2000.
49
Social/Ethical/Psychological Issues
Introduction
Social, psychological, and ethical issues are important factors to consider in regards to
information systems research because of the way they directly affect its users. Social
issues address the impacts of the computer technologies that are currently available on
organizations, individuals, and communities. Ethical issues involve privacy concerns,
moral dilemmas, and sensitive information. The psychological issues within technology
research deal with the cognitive and emotional states of people utilizing it. From these
areas of research, self-regulation, laws governing computer technology, sociological and
psychological well beings of people stems from these areas of research.
Most Important Theories
Some important theories, hypothesis, and models to come from this area of research are
the Media Richness Theory, Social Presence Theory, SIDE theory, Computers as Social
Actors, and Internet Addiction Theory.
Key Issues, Conflicts, and Major Research Problems
Amongst this body of literature, there are three major arguments that researchers uphold.
The first is the ethical use of using subjects over the Internet. When looking at the social
and psychological impacts of technology, a vast majority of research has been pertaining
to areas involving the Internet (e.g., e-commerce, distance learning, privacy issues).
Therefore, researchers raise the questions if it is considered ethical to monitor
transactional behaviors of consumers and/or read through e-mail messages and postings
found in chat rooms without the users consent. Another research problem is the ability to
be able to study technology that is always in flux.
50
Key Researchers
Mary J. Culnan
Contact Information
The McDonough School of Business, Georgetown University
Washington D.C., 20057-1008
(202) 687-3802; e-mail: culnanm@msb.edu
Research areas
Dr. Culnan’s research focus is on how information technology is impacted by social and
public policies and information privacy issues. She is currently working on the
Georgetown Internet Privacy Policy Study (GIPPS) and also looks at trends in consumer
attitudes and electronic marketing.
Sara Kiesler
Contact Information
3513 Newell-Simon Hall
Carnegie Mellon University
5000 Forbes Ave.
Pittsburgh, PA 15213-3891
(412) 268-2888; e-mail: kiesler@andrew.cmu.ecu
Research Areas
Dr. Kiesler has been currently working on the social, emotional, and behavioral impacts
of computing on individuals, families, and teams. She is best noted for her NSF
sponsored research regarding interdisciplinary collaborations and a system called
HomeNet, designed to study Internet usage among families. Other significant
contributions to the field by Dr. Kiesler include issues regarding e-mail flaming and
standards, formation of electronic groups, and social equalization and is currently a
Professor in the Human Computer Interaction Institute.
Robert Kling
Contact Information
School of Library and Information Science
Indiana University at Bloomington
107 S. Indiana Avenue
Bloomington, IN 47405-7000
(812) 855-9763, e-mail: kling@indiana.edu
Research areas
Social consequences of computerization and how it affects the public, computer ethics,
and personal privacy are major issues Dr. Kling focuses on. Currently he is working on
areas pertaining to scholarly communication and the use of electronic media to support it.
He has authored over 4 books pertaining to computerization, social impacts, and
controversies.
Donald Norman
Contact information
51
Apple Computer, Inc. MS 301-4UE
1 Infinite Loop, Cupertino, CA 95014 USA
(408) 862-5515; e-mail: dnorman@apple.com
Research areas
Dr. Norman is a leading researcher on human cognition and the interaction of technology
and society. He has taken his findings from the field of academics, leaving the
University of California, San Diego, and working for Apple Computer and being the
President of UNext.com Learning Systems. He is interested in how people utilize
technology and the impact that has on society.
Gary Olson
Contact Information
306A West Hall
550 E. University
Ann Arbor, MI 48109-1092
(734) 647-3576; e-mail: gmo@umich.edu
Research areas
Topics of specialization for Dr. Olson include computer support for collaboration issues,
policy formation, and decision-making. He is interested specifically in cognitive
psychology and human-computer-interaction. His background is in psychology and he
implements theories of psychology to social issues governing the use of computers. The
NSF, NICH, Apple computers, Arthur Andersen and Co, and Ameritech have funded his
research.
Lee Sproull
Contact Information
Leonard N. Stern School of Business
New York University
New York, New York
Research areas
Dr. Sproull’s research focuses on social and organizational implications of technology.
So far, she has published more then 50 books and articles on these topics. She is
currently working on the dynamics and consequences of electronic groups and
communities. Among her achievements are emphasizing connections between different
academic disciples and was a founding member of the Interdisciplinary department of
social and decision sciences at Carnegie Mellon University.
Key Papers
Birnbaum, M. H. (2000). Psychological experiments on the Internet. Academic Press:
San Diego, CA.
Gackenbach, J. (1998). Psychology and the Internet: Intrapersonal, interpersonal, and
transpersonal implications. Academic Press: San Diego, CA.
52
Kling, R. (1980). Social analyses of computing: Theoretical perspectives in recent
empirical research. Computing surveys, 12, 62-89.
This article examined empirical studies of computing use in organizations and in public
life. The roles of computer technologies for innovation, in the work life, in decision
making, and in influencing power are examined. In addition, this article also reviews the
privacy and social accountability issues. This articles groups analyses of the social
character and development of computing into two major perspectives: system rationalism
and segmented institutionalism.
Kraut, Kiesler, Mukhopadhyay, Scherlis, and Patterson. (1998). Social impact of the
Internet: What does it mean? Communications of the ACM (41), 12.
According to prior research involving studies regarding the HomeNet project, results
were found that people using the Internet incurred declines in social and psychological
well-being. Depression increased, communication between friends and family decreased,
and people overall felt lonelier even though the purpose for using the Internet was to
increase their interpersonal communication. Other outcomes of the study showed that
there is a difference between people who have positive versus negative attitudes about the
Internet. People with positive attitudes are not as concerned with their privacy, perceive
shopping by mail as beneficial, and have coping strategies for dealing with unwanted
mail. The authors give future research suggestions including focusing on characteristics
such as the sensitivity of the information, its source, its perceived relevance to the
original transaction, and whether disclosure reflects informed consent or results in a
potentially harmful outcome to the individual. This has implications for MIS research
involving e-commerce. Due to findings, MIS e-commerce research needs to take into
consideration people's attitudes about the Internet so that they can target ways in which to
assure people of their privacy and also encourage on-line shopping.
Norman, D. (1988). Psychology of the everyday things, Chapter 1, pp. 1-33. In Design of
Everyday Things.
Within the first chapter of his book, the concept of affordances, perceived and actual
properties of things, is introduced. Dr. Norman suggests that it is important to make
affordances visible, participate in natural mappings, taking advantage of physical
analogies and cultural understandings, and integrating user feedback. His discussion
revolves around taking a user-based center when designing anything from hardware to
software to tools. At times, MIS researchers focus on task and problem solving with little
regards to the user. The field of MIS research can benefit by reading this chapter as it
allows for awareness of user importance in design.
Turkle, S. (1995). Life on the screen: Identity in the age of the Internet. Simon and
Schuster.
Turkle's book is one of the first books to really describe ethnographically how people are
currently using the Internet and the possibilities of future use. She observes different online cultures (e.g., MOOs, MUDs, Chatrooms) and how they compare to real life
communities. This book can be beneficial for MIS researchers to read to use as a basic
understanding of how people are using new technologies and the social norms that are
already established on-line. They can in turn use this found knowledge by learning how
53
to redesign systems that are already in place to better serve its users. They can also
research into how people are using the systems already and project and propose future
research and better systems.
54
Supply Chain Management
Most Important Theories
To compete successfully in the global market, companies need to manage the
effectiveness and efficiency of the operations that manufacture and distribute their
products or services to their customers. Supply chain management deals with the
management of materials, information and financial flows in a network consisting of
suppliers, manufacturers, distributors, retailers, and customers. Many industries have
found it challenging to manage these flows efficiently and effectively.
There are three types of flows in a supply chain that require careful planning and
coordination. Material flows involve both physical product flows from suppliers to
customers through the chain as well as the reverse flows via product returns, servicing,
recycling, and disposal. Information flows involve order transmission and delivery status.
Financial flows involve credit terms, payment schedules, and consignment and title
ownership arrangements. These flows cut across companies and sometimes ownership
arrangements. These flows cut across companies and sometimes even industries [1].
Key Issues and Conflicts
The research of Supply Chain Management processes focuses on the coordination and
integration of the flows in a supply chain consisting of multiple sites and organizations
with multiple independent decision makers. The types of research in Supply Chain
Management can be:
Theoretical work motivated by real life problems and situations
Applications based on real cases
Conceptual work that provides a framework to analyze problems in industry
Empirical studies based on real data
Surveys of existing literature and industrial practice [1]
Key research issues and topics include: product and process designs for supply chain
management; structuring supply chains for mass customization; third party logistics;
outsourcing and contract manufacturing; supplier contracting; incentive and performance
measures; global supply chain management; quick response and cycle time reduction;
multi-product and multi-location production and inventory coordination; consolidation,
warehousing, scheduling and coordination of transportation and production flows; and
industry-wide supply chain integration.
References:
[1] “Editorial objectives for Supply Chain Management.” Management Science,
http://www.informs.org/Pubs/Mansci/statements.html#SUP
[2] Discussion with Dr. Danial Zeng, Department of MIS, University of Arizona,
December 12, 2000.
55
Key researchers
Gerard P. Cachon
University of Pennsylvania (2000 – present), Duke University (previous)
Email: gpc@mail.duke.edu
Webpage: www.duke.edu/~gpc
Research area: supply chain management; incentives in operations management,
electronic commerce
Fangruo Chen
Columbia University
Email: fc26@columbia.edu
Webpage: http://www.columbia.edu/cu/business/divisions/mgmtsci/chen.html
Research area: supply chain management
Hau L. Lee
Stanford University
Email: Hau.Lee@forsythe.stanford.edu
Webpage: www-ieem.stanford.edu/faculty/lee/lee.html
Research area: production and operations management, with special interest in
supply chain management, global logistics and distribution systems, inventory
management, information systems and logistics restructuring, manufacturing and
distribution interface, and manufacturing strategy.
Paul H. Zipkin
Duke University
Email: PaulZipkin@Duke.Edu
Webpage: http://faculty.fuqua.duke.edu/%7Ezipkin/bio/index.htm
Research area: operations management, inventory management, supply-chain
management and analysis
Key papers
Lee H.L., Padmanabhan V., and Whang S. “Information distortion in a supply chain: The
bullwhip effect.” Management Science, April 1997, Vol. 43, Iss. 4; pg. 546, 13 pgs.
A series of companies in a supply chain is considered, each of who orders from its
immediate upstream member. In this setting, inbound orders from a downstream member
serve as a valuable informational input to upstream production and inventory decisions. It
is claimed that the information transferred in the form of orders tends to be distorted and
can misguide upstream members in their inventory and production decisions. In
particular, the variance of orders may be larger than that of sales, and the distortion tends
to increase as one moves upstream - a phenomenon termed the bullwhip effect. Four
sources of the bullwhip effect are analyzed: demand signal processing, rationing game,
order batching, and price variations. Actions that can be taken to mitigate the detrimental
impact of this distortion are also discussed.
56
Cachon G.P., Lariviere M.A. “Capacity choice and allocation: Strategic behavior and
supply chain performance.” Management Science, August 1999, 45, 8, 1091-1109.
A simple supply chain in which a single supplier sells to several downstream retailers is
considered. The supplier has limited capacity, and retailers are privately informed of their
optimal stocking levels. If retailer orders exceed available capacity, the supplier allocates
capacity using a publicly known allocation mechanism, a mapping from retailer orders to
capacity assignments. It is shown that a broad class of mechanisms is prone to
manipulation; retailers will order more than they need to gain a more favorable
allocation. Another class of mechanisms induces the retailers to order exactly their needs,
thereby revealing their private information. However, there does not exist a truthinducing mechanism that maximizes total retailer profits. The supplier's capacity choice
is also considered. It is shown that a manipulable mechanism may lead the supplier to
choose a higher level of capacity than one would under a truth-inducing mechanism.
Nevertheless, one's choice will appear excessively restrictive relative to the prevailing
distribution of orders.
Cachon, G.P. “Managing supply chain demand variability with scheduled ordering
policies.” Management Science, June 1999, Vol. 45, 6, 843-857.
Supply chain demand variability is studied in a model with one supplier and N retailers
that face stochastic demand. Retailers implement scheduled ordering policies: Orders
occur at fixed intervals and are equal to some multiple of a fixed batch size. A method is
presented that exactly evaluates costs. Previous research demonstrates that the supplier's
demand variance declines as the retailers' order intervals are balanced, i.e., the same
number of retailers order each period. It is shown that the supplier's demand variance will
(generally) decline as the retailers' order interval is lengthened or as their batch size is
increased. Lower supplier demand variance can certainly lead to lower inventory at the
supplier. It is found that reducing supplier demand variance with scheduled ordering
policies can also lower total supply chain costs.
Chen F. “Decentralized supply chains subject to information delays.” Management
Science, August 1999, Vol. 45, Iss. 8, 1076-1091.
A supply chain whose members are divisions of the same firm are considered. The
divisions are managed by different individuals with only local inventory information.
Both the material and information flows in the supply chain are subject to delays. Under
the assumption that the division managers share a common goal to optimize the overall
performance of the supply chain, the optimal decision rules for the divisions are
characterized. The team solution reveals the role of information leadtimes in determining
the optimal replenishment strategies. It is shown that the owner of the firm can manage
the divisions as cost centers without compromising the systemwide performance. This is
achieved by using an incentive-compatible measurement scheme based on accounting
inventory levels. The impact of irrational behavior on supply chain performance is
investigated. It is important for the upstream members of the supply chain to have access
to accurate customer demand information.
Gavirneni S., Kapuscinski R., and Tayur S. "Value of information of capacitated supply
chains.” Management Science, January 1999, Vol. 45, Iss. 1; pg. 16, 9 pgs.
57
Information flow is incorporated between a supplier and a retailer in a two-echelon model
that captures the capacitated setting of a typical supply chain. Three situations are
considered: 1. A traditional model where there is no information to the supplier prior to a
demand to him except for past data, 2. The supplier knows the (s, S) policy used by the
retailer as well as the end-item demand distribution, and 3. The supplier has full
information about the state of the retailer. Order up-to policies continue to be optimal for
models with information flow for the finite horizon, the infinite horizon discounted and
the infinite horizon average cost cases. Study of these three models enables one to
understand the relationships between capacity, inventory, and information at the supplier
level, as well as how they are affected by the retailer's (S - s) values and end-item demand
distribution. The savings at the supplier due to information flow are estimated and when
information is most beneficial is studied.
58
Systems Analysis and Design
Key Issues
1.Software has become an integral part of world's economy. Software development and
deployment remain labor-intensive and intellectually demanding, requiring the best from
developers who must play a number of roles. There are still problems in the process of
making complex software.
2. Shortening cycle time for software projects with more efficiency.
3.Techniques for reuse of software.
4.New techniques for analysis and design- like UML. Further growth into the object
oriented approach.
Key Researchers
Tom DeMarco
Tom DeMarco is a principal of the Atlantic Systems Guild, a computer
systems think tank with offices in the US, Germany, and Great Britain. He
was the winner of the 1986 Warnier Prize for "lifetime contribution to the
field of computing. His work includes Peopleware: Productive Projects and
Teams and Software State-of-the-Art (with coauthor Tim Lister); Structured Analysis and
System Specification; Controlling Software Projects: Management, Measurement and
Estimation; Why Does Software Cost So Much? and Other Puzzles of the Information
Age; and a ground-breaking training video Productive Teams. He has written more than
100 articles and papers about management and the system development process. From his
early seminal work on structured analysis, to his later contributions in the areas of
software metrics and team building, Mr. DeMarco has established himself as a pioneer
and leader in the software profession. He is a member of the IEEE Software Editorial
Board, and was chosen to serve as guest editor for that journal's May, 1997 Special Issue
on Risk Management. He is a faculty member of Cutter Consortium
Grady Booch
Grady Booch is one of the leading software development methodologists in the
world. Along with Rational colleagues Ivar Jacobson and Jim Rumbaugh,
Grady developed the Unified Modeling Language (UML), the industrystandard language for specifying, visualizing, constructing, and documenting
the artifacts of software systems. The UML was officially adopted as a standard by the
Object Management Group (OMG) in 1997. His work centers primarily around complex
software systems. Booch is the author of four books, including "Object-Oriented Analysis
and Design," and "Object Solutions: Managing the Object-Oriented Project." He is a
member of AAAS, IEEE, and CPSR, and is both an ACM Fellow and Rational Fellow.
Currently he is the chief scientist at Rational Software.
59
Michael Fagan
During his development career, Michael created the inspection process for use
on his own projects. He created the Fagan Defect-Free Process, incorporating
Formal Process Definition, and reinforcing the Continuous Process
Improvement aspect of the Inspection Process. Using the inspection method, he
was also able to use its metrics to monitor projects and keep them on track. The
methodology developed by Michael Fagan is credited with dramatically reducing the
number of defects in software and hardware products, increasing the feature content per
release, shortening cycle time, increasing customer satisfaction, improving development
processes, accelerating SEI/CMM maturity in organizations, and significantly reducing
costs! He was the first software senior technical staff member in IBM's T.J. Watson
Research Laboratory; a member of the Corporate Technology Staff; and, one of the
founder members of the IBM Quality Institute. After creating the Inspection Process in
1972, he continued refining the methodology, incorporating Formal Process Definition,
and reinforcing the Continuous Process Improvement aspect of the Fagan Inspection
Process. Since 1989, when he formed Michael Fagan Associates, he has continued to
refine the methodology and has also found ways to help facilitate its very rapid
implementation in more than 60 organizations. From 1983 to 1985, Michael Fagan was a
Visiting Professor in the Department of Computer Science at the University of Maryland.
Michael Fagan Associates in located in Palo Alto, California.
Roger S. Pressman
Roger S. Pressman is an internationally recognized consultant and author in
software engineering. For over 25 years, he has worked as a software
engineer, manager, professor, author, and consultant, focusing on software
engineering issues. Dr. Pressman specializes in helping companies establish effective
software engineering practices. He is the developer of Process Advisor, the industry's
first self-directed software process improvement product, and Essential Software
Engineering, a comprehensive video curriculum. Dr. Pressman is the president of R.S.
Pressman and Associates. Dr. Pressman is the author of six books and many technical and
management articles. His book Software Engineering: A Practitioner's Approach, is the
world's most widely used software engineering textbook. He is also on the Editorial
Board of IEEE Software and is Series Advisor for the McGraw-Hill Systems Design and
Implementation Series. He is a member of the IEEE, ACM, and Tau Beta Pi.
Watts S. Humphrey
Watts S. Humphrey founded the Software Process Program of the Software
Engineering Institute (SEI) at Carnegie Mellon University. He is a Fellow of
the Institute and is a research scientist on its staff. His publications include
many technical papers and seven books. His most recent books are "Managing the
Software Process" (1989), "A Discipline for Software Engineering" (1995), "Managing
Technical People" (1996), "Introduction to the Personal Software Process" (1997), and
"Introduction to the Team Software Process" (2000). Humphrey was responsible for
developing improved software engineering process methods. He has continued to work
closely with software engineers in industry and government, helping them to implement
these improved methods. Before joining the SEI, Humphrey was with IBM for 27 years
60
in various technical and management positions. He is a Fellow of the SEI and the IEEE,
a member of the ACM, a past member of the Malcolm Baldridge national Quality Award
Board of Examiners, and a holder of five issued U.S. patents. He lives in Sarasota
Florida.
Edward Yourdon
Ed has worked in the computer industry for 36 years, beginning when Digital
Equipment Corporation innocently risked the downfall of Western civilization
by hiring him as a starry-eyed undergraduate student in 1964 to write the
FORTRAN math library for the PDP-5 and the assembler for the popular
PDP-8 minicomputer. During his career, he has worked on over 25 different mainframe
computers, and was involved in a number of pioneering computer technologies such as
time-sharing operating systems and virtual memory systems. He was a co-developer of
the Yourdon/Whitehead method of object-oriented analysis/design and the popular
Coad/Yourdon OO methodology. Ed is the author of over 250 technical articles; he has
also authored or coauthored 26 computer books since 1967.
Key Papers/Books
DeMarco, T. (1979). Structured Analysis and System Specification. Prentice-Hall.
This classic book of tools and methods for the analyst brings order and precision to the
specification process as it provides guidance and development of a structured
specification. Covers functional decomposition; data dictionary; process specification;
system modeling; structured analysis for a future system.
Pressman, R. S. (1997). Software Engineering: A Practitioner's Approach. McGraw-Hill.
This book explains all the important topics in software engineering. It is the most widely
used software engineering textbook in the world.
Yourdon, E., and Constantine, L. (1979). Structured Design. Prentice-Hall.
Grady Booch: Object-Oriented Development. TSE 12(2): 211-221 (1986)
According to the author, functional development methods suffer from several
fundamental limitations: they do not effectively address data abstraction and information
hiding, they are generally inadequate for problem domains with natural concurrency and
they are often not responsive to changes in the problem space.
Rick DeNatale, Grady Booch, Peter Coad, Dave A. Thomas, John Tibbets: The Role of
Methods and CASE in OO Development (Panel). OOPSLA 1992: 145
Barry W. Boehm, Tom DeMarco: Guest Editors' Introduction: Software Risk
Management. IEEE Software 14(3): 17-19 (1997)
Tom DeMarco: The Role of Software Development Methodologies: Past, Present, and
Future. ICSE 1996: 2-4
61
Dennis J. Frailey, "Reducing Cycle Time," Software Development, August 2000
According to this article the "cycle time" delays are caused by three fundamental
problems: variability; overly complex processes; and bottlenecks and constraints. The
author goes on to say that "a more fundamental symptom of cycle-time problems is
rework. The more you do things over, the more [work in process] you'll have, which
means you add cost and introduce delays.
Michael E. Fagan: Design and Code Inspections to Reduce Errors in Program
Development. IBM Systems Journal 38(2/3): 258-287 (1999)
Michael E. Fagan: Design and Code Inspections to Reduce Errors in Program
Development. IBM Systems Journal 15(3): 182-211 (1976)
Michael E. Fagan: Advances in Software Inspections. TSE 12(7): 744-751 (1986)
62
Telecommunication
Key Theories and Issues
Today's computer communication networks are based on a technology called packet
switching. Data to be communicated is broken into small chunks that are labeled to show
where they come from and where they are to go. Packets are forwarded from one
computer to another until they arrive at their destination. If any are lost, they are re-sent
by the originator. The recipient acknowledges receipt of packets to eliminate unnecessary
re-transmissions.
ARPANET, a pioneering work in the networking field, was initiated in 1969. Since then
numerous networking research was progressed to solve the problem of linking different
kinds of packet networks together without requiring the users or their computers to know
much about how packets moved from one network to another. A new set of computer
communication protocols, TCP/IP (Transmission Control Protocol and Internet Protocol),
that would allow multiple packet networks to be interconnected in a flexible and dynamic
way were developed to speed up the invention of what was later known as Internet. By
the mid-1980s there was sufficient interest in the use of Internet for business
implementation. An experimental electronic mail relay was built and put into operation in
1989 and its commercial use has exploded. The Internet has been experiencing
exponential growth in the number of networks, number of hosts, and volume of traffic.
One of the major forces behind the exponential growth of the Internet is a variety of new
capabilities in the network -- particularly directory, indexing, and searching services that
help users discover information in the vast sea of the Internet. Many of these services
have started as university research efforts and evolved into businesses. The World Wide
Web was first used in experimental form in 1989, and researchers developed a graphical
browser for the Web which, combined with hypertext, started a new telecommunication
era.
Future Work
It is risky to predict the future of something as dynamic as the Internet. It seems safe to
state that there will be a continuing explosion of new services. There is every reason to
believe that the Internet will transform education, business, government, and personal
activities in ways we cannot fully fathom. The main challenge would come from how to
predict the future networking trend and catch up with the rapid technical evolution while
there is almost no clue to predict for the future.
Key Researchers
Robert E. Kahn
(http://www.cnri.reston.va.us/bios/kahn.html)
Robert E. Kahn is president of the Corporation for National Research Initiatives (CNRI).
He worked at Bell Laboratories, and taught at MIT. He later joined Bolt Beranek and
63
Newman, DARPA. Dr. Kahn conceived the idea of open-architecture networking. He is a
co-inventor of the TCP/IP protocols and was responsible for originating DARPA's
Internet Program. Dr. Kahn also coined the term National Information Infrastructure
(NII) in the mid 1980s, widely known as the Information Super highway.
In his recent work, Dr. Kahn has been developing the concept of a digital object
infrastructure as a key middleware component of the NII. This notion is providing a
framework for interoperability of heterogeneous information systems and is being used in
several applications. He is a co-inventor of Knowbot programs, mobile software agents in
the network environment.
Dr. Kahn is a member of the National Academy of Engineering, a Fellow of the IEEE, a
Fellow of AAAI. He is also a member of the President's Information Technology
Advisory Committee. He is a recipient of numerous awards by his outstanding work.
Vinton G. Cerf ( http://www.stupi.se/Internauts/htmls/Vint-Cerf.html )
Vinton Cerf is senior Vice president of data architecture for MCI's Data and Information
Services Division, a unit of MCI Business Markets. Cerf recently was vice president of
the Corporation for National Research Initiatives (CNRI), where he conducted national
research efforts on information infrastructure technologies. Cerf co-developed the
computer networking protocol, TCP/IP, widely used in the industry and for
communications, and known collectively as the Internet.
From 1982 to 1986, Cerf was vice president of MCI Digital Information. He played a
major role in sponsoring the development of Internet-related data packet technologies.
Cerf is a fellow of the IEEE, ACM and AAAS, and the recipient of numerous awards and
commendations in connection with his work on the Internet. He also has served as
president of the Internet Society since 1992.
Ted Nelson
(http://www.sfc.keio.ac.jp/~ted)
Ted Nelson is currently a Visiting Professor of Environmental Information, Keio
University, Japan. He is best known for coining terms "hypertext" and "hypermedia,"
1963 (first published 1965), and as founder and pursuer of Project Xanadu, the name for
Ted Nelson's hypertext work since 1960.
Ted Nelson foresaw long ago the use of hypertext on a world-wide network. The
structures he and his group designed during the 1960s through 1980s were to make it
possible to annotate and reuse electronic documents, as well as create a new zone of
copyright. During the past four years in Japan, aided by colleagues, Nelson has been
redefining a component Xanadu for the new Internet environment, unpacking the one
unified idea of Xanadu into many separately achievable parts.
David Clark
(http://ana-www.lcs.mit.edu/anaweb/clark.html)
David Clark is senior research scientist of MIT Laboratory for Computer Science. He had
worked at Multics, and Arpanet managing the development of the ARPA network
protocols. He was one of the developers of key token ring LAN concepts. He currently
heads the Advanced Network Architecture research group. In the security area, Dr. Clark
developed an information security model that stresses integrity of data.
64
His current research interests are protocols and architectures for very large and very highspeed networks. Specific activities include the development of methods to support realtime traffic in the Internet, and new models of network service to support distributed
information systems.
Dr. Clark is a member of the IEEE and the ACM. He received the ACM SigComm award
and the IEEE Award for his work on the Internet. He chaired the Internet Activities
Board as well as a study committee of the National Academy of Sciences.
Deborah Estrin
(http://lecs.cs.ucla.edu/~estrin/)
Deborah Estrin is currently an Associate Professor of Computer Science Department of
University of Southern California. Dr. Estrin’s work has focused on the design of
network and routing protocols for very large, global, networks. Her current research
interests are in scalable multicast routing protocols, multicast-oriented reservation setup
protocols, inter-domain routing for global internets, adaptive routing to support
multimedia applications, and design tools and techniques for developing scalable network
protocols.
Dr. Estrin is a member of the ACM and AAAS. She has served on several panels for the
NSF, National Academy of Sciences/CSTB, ARPA, and Office of Technology
Assessment. In 1987, she received the National Science Foundation Presidential Young
Investigator Award for her research in network interconnection and security.
Roch Guerin
(http://www.seas.upenn.edu:8080/~guerin/)
Roch Guerin is currently the Alfred Fitler Moore Professor of Telecommunications
Networks in the University of Pennsylvania. After graduating from Caltech, he worked at
the IBM T.J. Watson Research Center.
His current research interests are in the areas of networking and Quality-of-Service, and
in particular the intersection of the above two areas. The issues of his interest include
randomization in QoS routing, advance reservations, and the impact of aggregation on
service guarantees and verification capabilities.
Key Articles
“Compatibility or Chaos in Communications”, Sanders, Ray W.; Cerf, Vinton G.;
Datamation, Barrington; Mar. 1976; Vol. 22, Issue 3.
A conflict is developing in data-communications in transmitting data between the
manufacture’s equipment and other brands. The users are pushing to erase as many major
incompatibilities as possible. Network Standardization would benefit both sides by giving
users more choice of equipment while opening new markets that would be economically
feasible due to resource sharing. Users must have a greater comprehension of networks.
An explanation of networks, access methods, layers of network access protocols, physical
link, and packet-level protocol is presented. Also discussed are the protocols on top of
protocols – link control header, packet header, information field, and control trailer,
graph and diagram.
65
“Information Processing Technology for Emergency Management”, Kahn, Robert E.
Information Society, New York; 1985.
Several information-processing technologies are capable of augmenting human
performance in handling a range of emergency situations. Technological areas that are
particularly important to emergency management are: communications, computers,
machine intelligence, and security. Both conventional and emerging technologies are
important in the area of communication networks. Some of the systems that have proved
useful in enhancing information collection, transmission, and selective processing are:
packet radio networks, satellite network technology, expert planning systems, Interneting,
and machine intelligence. Packet radio and multiple satellite technology, both based on
packet-switching, can make a considerable difference, and computer-based Internetwork
-systems will initially be most useful for communicating messages electronically. To be
effective, information technology must be integrated into daily patterns to make its use
comfortable and familiar.
“The Heart of Connection: Hypermedia Unified by Transclusion”, Nelson, Ted;
Association for Computing Machinery, New York; Aug 1995; Vol. 38, Issue 8.
The development of a system for massive parallel creative work and study is discussed.
The system is intended to be a technical, legal, and commercial basis for a worldwide
populist and participatory electronic literature of freely weaving screen transmedia republishable and quotable without restrictions - to the betterment of human
understanding and freedom of expression and access. The central idea is the concept of
transclusion, or reuse with original context available, through embedded shared
instancing (rather than duplicate bytes). Thus the user may intercompare contexts of what
is re-used, both for personal work and publication. The elements of transclusion are
discussed.
“Intradomain Qos Routing In IP Networks, A Feasibility And Cost/Benefit Analysis”,
Guerin, Roch, IEEE Network, 1999.
Constraint-based routing gradually becomes an essential enabling mechanism for a
variety of emerging network services. In this work the workers build on previous results
on the cost of QoS routing and investigate the performance/cost trade-offs involved in the
operation of a representative QoS routing architecture, elaborate on the constituents of
this cost, and identify the main methods for containing the cost that QoS routing incurs
on routers. The results show that the cost of QoS routing is not excessive and that there
exist operational configurations, which can achieve reasonable performance gains with
only a minimal increase in processing cost when compared to conventional best-effort
routing.
“An Analysis of TCP Processing Overhead”, David Clark; V. Jacobson, J. Romkey; H.
Salwen, IEEE Communications Magazine, June 1989, Vol. 27, No. 6.
The transport layer of the protocol suite, especially in connectionless protocols, has
considerable functionality and is typically executed in software by the host processor at
the end points of the network. It is thus considered a likely source of processing
overhead. However, a preliminary examination has suggested to the authors that other
aspects of networking may be a more serious source of overhead. To test this proposition,
66
a detailed study was made of the Transmission Control Protocol (TCP), the transport
protocol from the Internet protocol suite. In this set of protocols, the functions of
detecting and recovering lost or corrupted packets, flow control, and multiplexing are
performed at the transport level. The results of that study are presented. It is concluded
that TCP is in fact not the source of the overhead often observed in packet processing,
and that it could support very high speeds if properly implemented.
“Controls for Interorganization Networks”, Estrin, Deborah; IEEE Transactions On
Software Engineering, New York; Feb 1987; Vol. SE13, Issue 2.
Interorganization computer networks support person-to-person communication via
various methods. Because of most firms' desire for limited access of resources to
outsiders, interorganization networks (ION) have unique usage-control requirements. A
conceptual model for implementing usage control in IONs is described. Usage control
requirements in networks that cross organization boundaries are discussed. The analysis
indicates that category sets and nondiscretionary control mechanisms can be employed to
isolate strictly internal facilities from ION facilities and distinct IONs from one another.
Attention is then focused on the problem of authentification in IONs -- an essential
component of the proposed control mechanisms.
67
Workflow
Introduction
1. Definition - Workflow
The computerized facilitation or automation of a business process, in whole or part.
Workflow is often associated with Business Process Re-engineering, which is concerned
with the assessment, analysis, modeling, definition and subsequent operational
implementation of the core business processes of an organization (or other business
entity).
2. Definition - Workflow Management System
A system that completely defines, manages and executes “workflows” through the
execution of software whose order of execution is driven by a computer representation of
the workflow logic.
The Evolution of Workflow
The evolution of workflow as a technology has thus encompassed a number of different
product areas.
Image Processing
Document Management
Electronic Mail and Directories
Groupware Applications
Transaction-based Applications
Project Support Software
BPR and Structured System Design Tools
Separation of workflow functionality
Trends
Workflow Automation
Workflow Analysis
Workflow and E-Commerce
Workflow and AI
68
Key People
Christoph Bussler
Oracle Corporation, USA
Email: Christoph.Bussler@Informatik.Uni-Erlangen.DE
Webpage: http://www6.informatik.unierlangen.de/history/people/bussler.html
Research areas: Organizational policy management in workflow
management systems, generic workflow models, architecture of highperformance workflow management systems, and mobility aspects of workflow
management
Clarence Ellis
University of Colorado at Boulder
Email: Skip@Colorado.EDU
Webpage: http://rintintin.colorado.edu/~skip/
Research areas: Workflow technology, groupware, cognitive science
(group cognition), computer supported cooperative work, object oriented
systems, systems modeling, databases, group user interfaces, and
distributed systems.
Stefan Jablonski
University of Erlangen-Nuernberg, Germany
Email: Stefan.Jablonski@Informatik.Uni-Erlangen.DE
Webpage: http://www6.informatik.uni-erlangen.de/Staff/jablonski.html
Research areas: Workflow management, business process and enterprise
modeling, systems integration, transaction management, and database
management
Amit P. Sheth
University of Georgia
Email: amit@cs.uga.edu
Webpage: http://lsdis.cs.uga.edu/~amit/
Research areas: Interoperable information systems and enterprise
application integration (esp. workflow management), global information
systems (esp. management of heterogeneous digital media, information brokering, the
logical/semantic view of the web through use of broad variety metadata and ontologies).
J. Leon Zhao
University of Arizona
Email: lzhao@bpa.arizona.edu
Webpage: http://shell.bpa.arizona.edu/~lzhao/
Research areas: Development of database and workflow technologies and
their applications in electronic commerce, knowledge management, and
organizational process automation.
69
Key Papers
Dimitrios, Mark Hornick and Amith Sheith An Overview of Workflow Management:
From Process Modeling to Workflow Automation Infrastructure, Distributed and Parallel
Database, 3, 119-153 (1995)
Today's business enterprises must deal with global competition, reduce the cost of doing
business, and rapidly develop new services and products. To address these requirements
enterprises must constantly reconsider and optimize the way they do business and change
their information systems and applications to support evolving business processes.
Workflow technology facilitates these by providing methodologies and software to
support (i) business process modeling to capture business processes as workflow
specifications, (ii) business process reengineering to optimize specified processes, and
(iii) workflow automation to generate workflow implementations from workflow
specifications. This paper provides a high-level overview of the current workflow
management methodologies and software products. In addition, it discusses the
infrastructure technologies that can address the limitations of current commercial
workflow technology and extend the scope and mission of workflow management
systems to support increased workflow automation in complex real-world environments
involving heterogeneous, autonomous, and distributed information systems. In particular,
it discusses how distributed object management and customized transaction management
can support further advances in the commercial state of the art in this area.
2. Akhil Kumar; J Leon Zhao; Dynamic routing and operational controls in workflow
management systems; Management Science, Providence; Feb 1999; 45, 2; 253-273.
Businesses around the world are paying more attention to process management and
process automation to improve organizational efficiency and effectiveness. A general
framework for implementing dynamic routing and operational control mechanisms in
workflow management systems (WMS) is described. The framework consists of three
techniques: workflow control tables, sequence constraints, and event-based workflow
management rules. This approach offers several unique features that are missing in
commercial workflow management systems: 1. It provides more flexibility in process
modeling and control. 2. It permits rework on an ad hoc basis. 3. It handles exceptions to
routing and operational controls. 4. It exploits parallelism to increase system throughput
and response time. Finally, the workflow management techniques are applied to the case
of consumer loan management and compared with other approaches based on static
routing.
3. W.M.P. van der Aalst, The Application of Petri Nets to Workflow Management ,
Department of Mathematics and Computer Science reports, Eindhoven University of
Technology.
Workflow management promises a new solution to an age-old problem: controlling,
monitoring, optimizing and supporting business processes. What is new about workflow
management is the explicit representation of the business process logic which allows for
computerized support. This paper discusses the use of Petri nets in the context of
workflow management. Petri nets are an established tool for modeling and analyzing
processes. On the one hand, Petri nets can be used as a design language for the
70
specification of complex workflows. On the other hand, Petri net theory provides for
powerful analysis techniques which can be used to verify the correctness of workflow
procedures. This paper introduces workflow management as an application domain for
Petri nets, presents state-of-the-art results with respect to the verification of workflows,
and highlights some Petri-net-based workflow tools.
4. Christoph Bussler, Stefan Jablonski; Implementing Agent Coordination for Workflow
Management Systems Using Active Database Systems. RIDE-ADS 1994: 53-59
One crucial function of a workflow management system (WFMS) is to assign tasks to
users who are eligible to carry them out. Except in simple workflow scenarios, roles such
as secretary and manager are not a sufficient basis for determining eligibility.
Additionally, WFMSs are deployed not only in group settings by small companies but
also worldwide by large enterprises. Since local laws and business policies have to be
followed, task assignment policies for the same task generally differ from country to
country and, therefore, must be specified locally. The Policy Resolution Architecture
(PRA) model provides more generality and expressiveness than role models do and at the
same time supports the independent specification of task assignment policies in different
parts of an enterprise. PRA can be used to model arbitrary organization structures and to
define realistic task assignment (eligibility) rules by means of precisely defined
organizational policies. Thus, PRA provides real-world organizations with a precise,
simple means of expressing their complex task assignment policies.
71
Appendix A
Name
Lynda M Applegate
Yannis Bakos
Frank Biocca
Grady Booch
Organization
Harvard University
New York University
Michigan State
University
Gerard P Cachon
Vinton G. Cerf
University of
California, Los Angeles
Massachusetts Institute
of Technology
Oracle Corporation
University of
Pennslvnia
MCI
Fangruo Chen
Columbia University
Hsinchun Chen
University of Arizona
Massachusetts Institute
of Technology
University of
Massachusetts,
Amherst
Georgetown University
Christine L. Borgman
Erik Brynjolfsson
Christoph Bussler
David Clark
W. Bruce Croft
Mary J. Culnan
Thomas Davenport
Tom DeMarco
Peter J. Denning
Jerry DeSanctis
Vinton G. Cerf
Moshe Dror
Clarence Ellis
Deborah Estrin
Michael Fagan
Edward A. Feigenbaum
Marshall Fisher
R. Brent Gallupe
Seymour E. Goodman
Roch Guerin
Watts S. Humphrey
Edward A. Fox
Boston University
George Mason
University
Duke University
MCI
University of Arizona
University of Colorado
at Boulder
University of Southern
California
Stanford University
University of
Pennsylvania
Queens University
Georgia Institute of
Technology
University of
Pennsylvania
Virginia Polytechnic
Institute and State
University
Research Field
E-Commerce
E-Commerce
CMC/HCI/Communication/Visualiz
ation
Systems Analysis and Design
Knowledge Management /
Information Retrieval
Information Economics
Workflow
Operations Research/Supply Chain
Management
Telecommunication
Operations Research/Supply Chain
Management
Artificial Intelligence/Knowledge
Management
Knowledge Management /
Information Retrieval
Telecommunication
Information Retrieval
Social/Ethical/psychological issues
Information Retrieval
Systems Analysis and Design
Computing Policy
Group Support Systems
Telecommunication
Operations Research
Workflow
Telecommunication
Systems Analysis and Design
Artificial Intelligence/Knowledge
Management
Operations Research
Group Support Systems
Computing Policy
Telecommunication
Systems Analysis and Design
Information Retrieval
72
Knowledge Management /
Information Retrieval
Knowledge Management /
Information Retrieval
Stefan Jablonski
Sirkaa L. Jarvenpaa
Ellis Johnson
Karen Sparck Jones
Robert E. Kahn
Sara Kiesler
Won Kim
Robert Kling
Robert Kraut
Charles H. Kriebel
Hau L. Lee
Stuart E. Madnick
Gary Marchionini
John McCarthy
Haim Mendelson
Tridas Mukhopadhyay
Ted Nelson
Theodor Holm Nelson
George Nemhauser
Peter G. Neumann
Jakob Nielsen
Eli M. Noam
Donald Norman
Jay F. Nunamaker, Jr.
University of ErlangenNuernberg, Germany
University of Texas at
Austin
Georgia Institute of
Technology
University of
Cambridge
Corporation for
National Research
Initiatives
Carnegie Mellon
University
Cyber Database
Solutions, Inc.
Indiana University at
Bloomington
Carnegie Mellon
University
Carnegie Mellon
University
University of Stanford
Massachusetts Institute
of Technology
Stanford University
Stanford University
Carnegie Mellon
University
Keio University, Japan
Keio University
Georgia Institute of
Technology
Daniel E. O'Leary
Columbia University
Apple Computer, Inc.
University of Arizona
University of Southern
California
Gary M. Olson
University of Michigan
Judy Olson
University of Michigan
Massachusetts Institute
of Technology
Massachusetts Institute
of Technology
Wanda J. Orlikowski
James B. Orlin
Roger S. Pressman
Sudha Ram
University of Arizona
Workflow
Group Support Systems
Operations Research
Information Retrieval
Telecommunication
Group Support Systems
Social/Ethical/psychological
issues
Database
Social/Ethical/psychological issues
CMC/HCI/Communication/Visualiz
ation
Computing Policy
Information Economics
Operations Research/Supply Chain
Management
Database
Information Retrieval
Artificial Intelligence/Knowledge
Management
E-Commerce
E-Commerce
Telecommunication
Artificial Intelligence/Knowledge
Management
Operations Research
Computing Policy
CMC/HCI/Communication/Visualiz
ation
Computing Policy
Social/Ethical/psychological issues
Group Support Systems
Knowledge Management /
Information Retrieval
Knowledge Management /
Information Retrieval
Group Support Systems
Group Support Systems
Operations Research
Systems Analysis and Design
Database
73
Information Economics
Social/Ethical/psychological
issues
CMC/HCI/Communication/
Visualization
Raj Reddy
Gerard Salton (1927-1995)
Jerome Howard Saltzer
Omar El Sawy
Roger c. Schank
Amit P. Sheth
Ben Shneiderman
Barbara Simons
Herbert A. Simon
Lee Sproull
Sherry Turkle
Douglas R. Vogel
Joseph Walther
Suzie Weisband
Andrew B. Whinston
J. Leon Zhao
Paul H. Zipkin
Vladimir Zwass
Carnegie Mellon
University
Artificial Intelligence/Knowledge
Management
Cornell University
Massachusetts Institute
of Technology
University of Southern
California
Northwestern
University
University of Georgia
Information Retrieval
University of Maryland
Carnegie Mellon
University
New York University
Massachusetts Institute
of Technology
City University of
Hong Kong
Rensselaer Polytechnic
Institute
University of Arizona
University of Texas at
Austin
University of Arizona
Duke University
Fairleigh Dickinson
University
Knowledge Management /
Information Retrieval
Computing Policy
Knowledge Management /
Information Retrieval
Artificial Intelligence/Knowledge
Management
Workflow
CMC/HCI/Communication/Visualiz
ation
Computing Policy
Artificial Intelligence/Knowledge
Management
Social/Ethical/psychological issues
CMC/HCI/Communication/Visualiz
ation
Group Support Systems
CMC/HCI/Communication/Visualiz
ation
CMC/HCI/Communication/Visualiz
ation
E-Commerce
Workflow
Operations Research/Supply Chain
Management
E-Commerce
74
Information Economics